through all of that, setting it up if you want to. PowerBI Pro purchasing of
you want to. PowerBI Pro purchasing of that is not required to complete this
that is not required to complete this course whatsoever. But it is good for
course whatsoever. But it is good for you to go through and understand how to
you to go through and understand how to use this because like I said, you're
use this because like I said, you're going to be using this in the real
going to be using this in the real world.
All right, before we just dive head first in the PowerBI service and explain
first in the PowerBI service and explain that, you first need to understand what
that, you first need to understand what are the different methods to share a
are the different methods to share a PowerBI report. And overall, I found
PowerBI report. And overall, I found that there's two main ones. The first is
that there's two main ones. The first is sharing the PowerBI file itself. And the
sharing the PowerBI file itself. And the second one that we're going to get to
second one that we're going to get to for the remainder of this is the PowerBI
for the remainder of this is the PowerBI service. I do want to let you know that
service. I do want to let you know that this is an option. With the PowerBI file
this is an option. With the PowerBI file or PowerBI report, there's no account
or PowerBI report, there's no account needed. You don't need any type of
needed. You don't need any type of license or prolic. The con, however, is
license or prolic. The con, however, is you as obviously building it need a
you as obviously building it need a PowerBI desktop and whoever you send it
PowerBI desktop and whoever you send it to has to go and download PowerBI
to has to go and download PowerBI desktop. So this PowerBI report that we
desktop. So this PowerBI report that we have has everything we need in order to
have has everything we need in order to send it. This data and everything is
send it. This data and everything is actually all inside of it. So we only
actually all inside of it. So we only need to send this file. Going to the
need to send this file. Going to the file of jobs dashboard. I just want to
file of jobs dashboard. I just want to show it's about 19 megabytes with all
show it's about 19 megabytes with all the data. It's not that big. So it is
the data. It's not that big. So it is possible for you to go through and
possible for you to go through and actually just email to somebody else and
actually just email to somebody else and then for the open it up and be able to
then for the open it up and be able to use this. However, whenever I was
use this. However, whenever I was working for like Mr. beast. We use the
working for like Mr. beast. We use the PowerBI service in order for everybody
PowerBI service in order for everybody on my team to go to a central location
on my team to go to a central location location to access a different PowerBI
location to access a different PowerBI dashboard. It ensures that there's a
dashboard. It ensures that there's a single source of truth and so everybody
single source of truth and so everybody can access the same thing and ensuring
can access the same thing and ensuring that they don't have something that's
that they don't have something that's out ofd, some file that shouldn't be
out ofd, some file that shouldn't be used anymore. The drawback to this is
used anymore. The drawback to this is that anybody that needs access to this
that anybody that needs access to this needs to have a PowerBI account.
All right, so let's jump into the PowerBI service. Once again, you don't
PowerBI service. Once again, you don't have an account yet, so you can't log
have an account yet, so you can't log into this. This is more of a demo
into this. This is more of a demo purpose, so that way if you do or don't
purpose, so that way if you do or don't decide to pursue getting an account, you
decide to pursue getting an account, you know what you're actually getting
know what you're actually getting yourself into. Anyway, I'm here at
yourself into. Anyway, I'm here at app.powerbi.com.
app.powerbi.com. This is my home screen and similar to
This is my home screen and similar to how PowerBI looks like you open it up,
how PowerBI looks like you open it up, they have things like, hey, you can
they have things like, hey, you can scroll down here and get to your recent
scroll down here and get to your recent files. So, one of the key features
files. So, one of the key features inside of here is I can access a report.
inside of here is I can access a report. Let's actually look at our dashboard.
Let's actually look at our dashboard. Uh, future Luke has uploaded it into the
Uh, future Luke has uploaded it into the system and it's available inside of
system and it's available inside of here. Anyway, it's displaying all the
here. Anyway, it's displaying all the different information that we had
different information that we had previously. I can even interact with it
previously. I can even interact with it like we did and it still has all the
like we did and it still has all the different information that we need with
different information that we need with it. In here, I can do other things by
it. In here, I can do other things by going up to the file menu. I could
going up to the file menu. I could download this file and use it locally. I
download this file and use it locally. I can manage permissions of who has access
can manage permissions of who has access to this dashboard within my company. I
to this dashboard within my company. I could waste a bunch of paper and print
could waste a bunch of paper and print it. And I can even do this, which we're
it. And I can even do this, which we're going to be doing later, is embed the
going to be doing later, is embed the report. Specifically, I like to do this
report. Specifically, I like to do this of publish to web. This provides us with
of publish to web. This provides us with an embedded code that we can either link
an embedded code that we can either link that we can send something like an email
that we can send something like an email or you could post it inside of a
or you could post it inside of a website. I'm going to go ahead and just
website. I'm going to go ahead and just copy this link. And then here inside of
copy this link. And then here inside of an incognito window, so I'm not logged
an incognito window, so I'm not logged into anything in this window, I can
into anything in this window, I can paste in this link. And then when I
paste in this link. And then when I navigate to it, I'm able to access this
navigate to it, I'm able to access this dashboard and anybody with this link can
dashboard and anybody with this link can access the dashboard, go through it, and
access the dashboard, go through it, and actually filter down, use tool tips, and
actually filter down, use tool tips, and actually be able to interact with our
actually be able to interact with our data. Now, there's a few other features
data. Now, there's a few other features I want to call out real quick inside the
I want to call out real quick inside the PowerBI service. Over here on the lefth
PowerBI service. Over here on the lefth hand side we have create. This gives you
hand side we have create. This gives you the option to build PowerBI reports
the option to build PowerBI reports without even installing the desktop and
without even installing the desktop and doing it here. Do not do this. Highly
doing it here. Do not do this. Highly don't recommend it. It's not as
don't recommend it. It's not as functional. Build in the desktop app and
functional. Build in the desktop app and then upload to the service. Next is
then upload to the service. Next is browse to let you go through any
browse to let you go through any recents, favorites or even shared with
recents, favorites or even shared with you. Then is probably the most important
you. Then is probably the most important is workspaces. And workspaces is what I
is workspaces. And workspaces is what I create in order to share with certain
create in order to share with certain groups. Now I have my own workspace
groups. Now I have my own workspace where I maintain all the different
where I maintain all the different dashboards that I have and I could give
dashboards that I have and I could give people access to this although that's
people access to this although that's not a good idea. Instead what I want to
not a good idea. Instead what I want to do is I can create other workspaces by
do is I can create other workspaces by creating this new workspace and I can
creating this new workspace and I can store in this one here called data job
store in this one here called data job postings different dashboards within it
postings different dashboards within it that I want people to have access to. So
that I want people to have access to. So this was the dashboard we built which
this was the dashboard we built which we're going to get to the end of this of
we're going to get to the end of this of actually uploading to the PowerBI
actually uploading to the PowerBI service. But I can have other reports as
service. But I can have other reports as well like this one here that connects to
well like this one here that connects to my BigQuery database. And remember we
my BigQuery database. And remember we had 3.6 million jobs in that database.
had 3.6 million jobs in that database. Anyway, this dashboard on the service
Anyway, this dashboard on the service has a direct query access to that
has a direct query access to that database in this dashboard. Pretty neat.
database in this dashboard. Pretty neat. Anyway, I have it all centralized in
Anyway, I have it all centralized in that one workspace that I can give
that one workspace that I can give certain people access to. All I have to
certain people access to. All I have to do is go into that workspace, go into
do is go into that workspace, go into manage access, and add or remove any
manage access, and add or remove any type of people or groups into here. One
type of people or groups into here. One note with this, those that have a free
note with this, those that have a free license, which we're about to get into
license, which we're about to get into license types, but those that have a
license types, but those that have a free license, you won't have the ability
free license, you won't have the ability to create new workspaces. You'll only
to create new workspaces. You'll only have my workspace. But that's actually a
have my workspace. But that's actually a great segue.
So, what are your options to get access to the PowerBI service? Well, they have
to the PowerBI service? Well, they have a few different options that you'll be
a few different options that you'll be able to choose from. The first is free.
able to choose from. The first is free. And like I mentioned, you're going to
And like I mentioned, you're going to need either a work or school email
need either a work or school email account. You won't be able to use any
account. You won't be able to use any personal email accounts. They won't let
personal email accounts. They won't let you use this to create a free account.
you use this to create a free account. Additionally, with the free account, not
Additionally, with the free account, not only can you not create workspaces, but
only can you not create workspaces, but you also won't be able to share any of
you also won't be able to share any of your work. So, that share to web not
your work. So, that share to web not going to be able to do. Basically,
going to be able to do. Basically, you're really limited. Next up is the
you're really limited. Next up is the pro license, and I feel it's the perfect
pro license, and I feel it's the perfect license. If you want to get anything, I
license. If you want to get anything, I would get that one. And that allows you
would get that one. And that allows you to share and collaborate with others.
to share and collaborate with others. Not only can you build reports, but you
Not only can you build reports, but you can also share them to the web like I
can also share them to the web like I demonstrated earlier. Now, the other two
demonstrated earlier. Now, the other two of preamp per user and then also
of preamp per user and then also embedded. Those are just more advanced
embedded. Those are just more advanced PowerBI that we're not even going to get
PowerBI that we're not even going to get into that more has to deal with when
into that more has to deal with when you're dealing with even larger data
you're dealing with even larger data sets or more frequent data refreshes.
sets or more frequent data refreshes. But based on what we're just trying to
But based on what we're just trying to accomplish with this course, that's way
accomplish with this course, that's way out of the scope of what you'd need.
out of the scope of what you'd need. However, this would be something that
However, this would be something that you may need to consider in the real
you may need to consider in the real world when you get to a company and
world when you get to a company and you're working with some really large
you're working with some really large data sets.
All right, the remainder of this lesson is going to be going through actually
is going to be going through actually purchasing the PowerBI Pro license,
purchasing the PowerBI Pro license, setting it up, and then uploading a
setting it up, and then uploading a dashboard so that way we can share with
dashboard so that way we can share with this. As a reminder, this portion is
this. As a reminder, this portion is completely optional. In no way do you
completely optional. In no way do you need to purchase a license to complete
need to purchase a license to complete this course. Mainly, this is just doing
this course. Mainly, this is just doing this for a learning experience in order
this for a learning experience in order for you to see what is actually done and
for you to see what is actually done and what you can accomplish with the PowerBI
what you can accomplish with the PowerBI service. For the remainder of the
service. For the remainder of the course, you will have the option to
course, you will have the option to share your dashboard to the PowerBI
share your dashboard to the PowerBI service, but I'll also be providing
service, but I'll also be providing other methods of how you can share the
other methods of how you can share the file instead in order to be able to
file instead in order to be able to share your work. All right, so let's let
share your work. All right, so let's let me get into it of purchasing this Pro
me get into it of purchasing this Pro license. First thing you got to do is
license. First thing you got to do is verify you're not a robot. And then
verify you're not a robot. And then you'll need to go through and after you
you'll need to go through and after you put in your email, can be a personal
put in your email, can be a personal email. You need to put in all your
email. You need to put in all your different personal information. After
different personal information. After this, they're going to be setting you up
this, they're going to be setting you up with a custom domain name because you're
with a custom domain name because you're not going to use your personal email
not going to use your personal email account to sign in. You're actually
account to sign in. You're actually going to be using something they
going to be using something they assigned to you to sign in further. So,
assigned to you to sign in further. So, don't lose this email that they give
don't lose this email that they give you. And also, don't forget the password
you. And also, don't forget the password that they that you make for this. After
that they that you make for this. After you've gone through and applied all your
you've gone through and applied all your payment information to set up those
payment information to set up those recurring monthly payments, they do want
recurring monthly payments, they do want you to set up a security measure of
you to set up a security measure of using the authenticator app from
using the authenticator app from Microsoft to verify that it's actually
Microsoft to verify that it's actually you. Anyway, this will require you to
you. Anyway, this will require you to log onto your phone and actually use
log onto your phone and actually use that to verify you are who you are.
that to verify you are who you are. Anytime you log into PowerBI, you're
Anytime you log into PowerBI, you're going to have to do this. Once that's
going to have to do this. Once that's done, you'll have a confirmation method
done, you'll have a confirmation method giving you that email in case you didn't
giving you that email in case you didn't write down earlier and you can jump
write down earlier and you can jump right in of start using PowerBI Pro. And
right in of start using PowerBI Pro. And so let's jump right in. And it's going
so let's jump right in. And it's going to take us immediately to the admin
to take us immediately to the admin center within Microsoft 365. If we want
center within Microsoft 365. If we want to get to PowerBI, we go to the corners
to get to PowerBI, we go to the corners up to the left and we click PowerBI. And
up to the left and we click PowerBI. And then bam, we're here inside the service
then bam, we're here inside the service itself. All right. So we've already done
itself. All right. So we've already done a quick tour of this. Now what we need
a quick tour of this. Now what we need to do is we need to link our PowerBI,
to do is we need to link our PowerBI, our desktop app to this service.
So now I'm here back inside of our desktop app. We want to actually go
desktop app. We want to actually go through and sign in. So up in that top
through and sign in. So up in that top top right hand corner, I'm going to
top right hand corner, I'm going to click sign in. Going to put in the email
click sign in. Going to put in the email account that they gave me for my PowerBI
account that they gave me for my PowerBI Pro account. And then after entering my
Pro account. And then after entering my credentials of my login and also my
credentials of my login and also my password, I need to then go to the
password, I need to then go to the authenticator app and inside of here
authenticator app and inside of here insert the number that's on the screen
insert the number that's on the screen in order to access. I'm going to select
in order to access. I'm going to select yes that I wanted to have access to all
yes that I wanted to have access to all apps. But now we want to get this
apps. But now we want to get this PowerBI dashboard into the service.
PowerBI dashboard into the service. Specifically here I am inside the
Specifically here I am inside the service and underneath workspaces we can
service and underneath workspaces we can either upload it into my workspace or I
either upload it into my workspace or I have this one called data job postings.
have this one called data job postings. If you don't you can create a workspace
If you don't you can create a workspace if you did create that pro license by
if you did create that pro license by just clicking new workspace and then
just clicking new workspace and then from there all you got to really do is
from there all you got to really do is put a name for that. You can even assign
put a name for that. You can even assign an image. Click apply and you got this
an image. Click apply and you got this new workspace. Anyway, we're going to be
new workspace. Anyway, we're going to be using my data jobs postings one. So,
using my data jobs postings one. So, feel free to copy that name if you want.
feel free to copy that name if you want. Right now, I only have one dashboard
Right now, I only have one dashboard inside of here. And just a quick note
inside of here. And just a quick note with this right here, it says, hey, this
with this right here, it says, hey, this is the report. So, this is the actual
is the report. So, this is the actual dashboard itself. When I navigate to it,
dashboard itself. When I navigate to it, I can actually see it here. And then the
I can actually see it here. And then the other one is the semantic model.
other one is the semantic model. Basically, it's the data set, all the
Basically, it's the data set, all the data and all the different information,
data and all the different information, the metadata behind it. So, anytime you
the metadata behind it. So, anytime you upload anything, you're going to see
upload anything, you're going to see two. You're going to see the report and
two. You're going to see the report and the semantic model. Anyway, back in the
the semantic model. Anyway, back in the PowerBI app, I can come up here now. I
PowerBI app, I can come up here now. I know I want it up there. I'm logged in.
know I want it up there. I'm logged in. I'm going to click publish and it's
I'm going to click publish and it's going to say, hey, select a destination.
going to say, hey, select a destination. I can either go to my workspace or that
I can either go to my workspace or that one I created of data jobs postings. I'm
one I created of data jobs postings. I'm going to do that. Select select. And now
going to do that. Select select. And now it's going to go through actually
it's going to go through actually uploading it to the service. After less
uploading it to the service. After less than a minute, you'll get the success
than a minute, you'll get the success message and you then from there can open
message and you then from there can open it inside of PowerBI. Let's open another
it inside of PowerBI. Let's open another tab and then bam, here is the dashboard
tab and then bam, here is the dashboard inside of here. And looks like it's
inside of here. And looks like it's working just fine. Filtering all the
working just fine. Filtering all the different data has everything in it.
different data has everything in it. Good to go.
Now, what happens now if you want to go ahead and go into file embed reports and
ahead and go into file embed reports and you actually want to publish this bad
you actually want to publish this bad boy to the web. Well, for you, if you've
boy to the web. Well, for you, if you've just logged in, you're not going to be
just logged in, you're not going to be able to do it unless you enable some
able to do it unless you enable some extra features. Don't worry, they don't
extra features. Don't worry, they don't cost any money. We just have to actually
cost any money. We just have to actually go through and actually set it up.
go through and actually set it up. Anyway, we need to go into settings up
Anyway, we need to go into settings up in the top right hand corner and then
in the top right hand corner and then scroll down until we see something
scroll down until we see something called the admin portal. That's where we
called the admin portal. That's where we want to go to. This has all the
want to go to. This has all the different settings and control at a high
different settings and control at a high level for the service. The first thing
level for the service. The first thing we're going to come over to this filter
we're going to come over to this filter on the right hand side and we're going
on the right hand side and we're going to search for publish to web. I'm going
to search for publish to web. I'm going to go ahead and click this arrow to open
to go ahead and click this arrow to open it up. Right now, mine's enabled. Most
it up. Right now, mine's enabled. Most likely yours is not enabled. I think
likely yours is not enabled. I think it's disabled actually. Let's see. Yeah,
it's disabled actually. Let's see. Yeah, it's disabled. You want to enable it.
it's disabled. You want to enable it. So, make sure that's enabled so you can
So, make sure that's enabled so you can actually publish to the web. You should
actually publish to the web. You should allow it for all users and it should be
allow it for all users and it should be for the entire organization. After you
for the entire organization. After you do this, click apply. Now, there's one
do this, click apply. Now, there's one other setting you have to do as well.
other setting you have to do as well. This is under advanced networking
This is under advanced networking specifically under tenant level private
specifically under tenant level private link. This needs to be disabled. So, if
link. This needs to be disabled. So, if it's not if you're in your case, it's
it's not if you're in your case, it's probably enabled. you need to disable it
probably enabled. you need to disable it anyway. Whenever you disable it, click
anyway. Whenever you disable it, click apply. Once again, with like the last
apply. Once again, with like the last one, these things take up to 15 minutes
one, these things take up to 15 minutes to complete. So, you're not going to be
to complete. So, you're not going to be able to publish your report just yet.
able to publish your report just yet. You can try. It's probably not going to
You can try. It's probably not going to work. Didn't work for me. It took about
work. Didn't work for me. It took about 15 minutes. Anyway, let's assume 15
15 minutes. Anyway, let's assume 15 minutes passed. Okay. So, here I'm on
minutes passed. Okay. So, here I'm on the data jobs dashboard. Going to go to
the data jobs dashboard. Going to go to file, embed report, and publish to web.
file, embed report, and publish to web. It's going to ask me or ask it's going
It's going to ask me or ask it's going to basically say, "Hey, this link's
to basically say, "Hey, this link's going to include on a public website."
going to include on a public website." That's okay. Yep. I'm going to click
That's okay. Yep. I'm going to click continue. And it's going to make sure
continue. And it's going to make sure that hey, make sure you're not
that hey, make sure you're not publishing any confidential proprietary
publishing any confidential proprietary pro proprietary information. So if you
pro proprietary information. So if you have any confidential data, this is not
have any confidential data, this is not confidential. You can share it, but
confidential. You can share it, but especially if you're dealing with work
especially if you're dealing with work type of data, you don't want to be doing
type of data, you don't want to be doing this. This is specifically for open free
this. This is specifically for open free data. And now with this, I have two
data. And now with this, I have two different links like we talked about
different links like we talked about before. I can just copy that link and
before. I can just copy that link and then even going into this browser right
then even going into this browser right here, I can see that whenever I enter
here, I can see that whenever I enter the link in, it's live on the web, free
the link in, it's live on the web, free for anybody to access. So that's an
for anybody to access. So that's an overview of PowerBI service and how you
overview of PowerBI service and how you can go about sharing something like this
can go about sharing something like this dashboard. We do now have a quiz for the
dashboard. We do now have a quiz for the practice problems to go through and test
practice problems to go through and test your knowledge and make sure you
your knowledge and make sure you understand how to use the PowerBI
understand how to use the PowerBI service. Now, in the next chapter, we're
service. Now, in the next chapter, we're going to be jumping into building
going to be jumping into building visualizations. We're going to be
visualizations. We're going to be tackling all the different ones. super
tackling all the different ones. super excited about that. With that, I'll see
excited about that. With that, I'll see you there.
Welcome to chapter 2. We're going to be covering visualizations. We're going to
covering visualizations. We're going to be walking through every single type
be walking through every single type that you're actually making here and
that you're actually making here and which ones are actually useful. Now, in
which ones are actually useful. Now, in this lesson here, we're going over
this lesson here, we're going over column and bar charts. But before that,
column and bar charts. But before that, we really need to understand what we're
we really need to understand what we're going to be covering for this entire
going to be covering for this entire chapter. So, let's jump into my
chapter. So, let's jump into my computer.
So let's dive into the PowerBI report that we're going to be using for this
that we're going to be using for this chapter here in the second folder for
chapter here in the second folder for visualizations. We just have a single
visualizations. We just have a single file for this. When you open this up,
file for this. When you open this up, you should be navigated first to this
you should be navigated first to this homepage. And these are actually
homepage. And these are actually different buttons that you can use to
different buttons that you can use to navigate to the different buttons. You
navigate to the different buttons. You just have to press control and then
just have to press control and then click and then you can navigate to
click and then you can navigate to anything. And then if I want to go back
anything. And then if I want to go back to that home menu, I have this
to that home menu, I have this convenient home menu icon up here. Once
convenient home menu icon up here. Once again, I have to press control and then
again, I have to press control and then click and it navigates me back. We'll be
click and it navigates me back. We'll be covering buttons in the last lesson of
covering buttons in the last lesson of the chapter, but let's look what we're
the chapter, but let's look what we're going to cover now. In this lesson,
going to cover now. In this lesson, we're going to be covering column and
we're going to be covering column and bar charts. We're going to go over four
bar charts. We're going to go over four different examples and distinguish
different examples and distinguish between what is a bar chart and what is
between what is a bar chart and what is a column chart. Second lesson is going
a column chart. Second lesson is going to use time series data in order to make
to use time series data in order to make line charts and also area charts. The
line charts and also area charts. The third lesson is going to go into common
third lesson is going to go into common charts that I find myself using beyond
charts that I find myself using beyond those other ones that we just covered in
those other ones that we just covered in lesson one and two, specifically pie
lesson one and two, specifically pie charts, donut charts, scatter plots, and
charts, donut charts, scatter plots, and tree maps. Lesson four, we'll get into
tree maps. Lesson four, we'll get into maps. And PowerBI has three different
maps. And PowerBI has three different options that you can choose through for
options that you can choose through for this. And then lesson five, we'll get
this. And then lesson five, we'll get into some uncommon charts. Mainly, I'm
into some uncommon charts. Mainly, I'm just going to show these in order for
just going to show these in order for you to understand what charts you
you to understand what charts you probably shouldn't be using most of the
probably shouldn't be using most of the time, but have familiarity with it.
time, but have familiarity with it. Lesson six, we'll get into building not
Lesson six, we'll get into building not only tables, but also matrices. Matrices
only tables, but also matrices. Matrices allow us to actually dive into the data
allow us to actually dive into the data a little bit more uh in depth. Anyway,
a little bit more uh in depth. Anyway, we'll also be covering with this
we'll also be covering with this conditional formatting. So, we'll just
conditional formatting. So, we'll just do things like do these color icons or
do things like do these color icons or color bars. Lesson seven will be on
color bars. Lesson seven will be on cards because everybody loves a good
cards because everybody loves a good card that tells a good data point. And
card that tells a good data point. And then lesson eight will be on slicers
then lesson eight will be on slicers because we don't always want to use just
because we don't always want to use just filters alone to actually filter down
filters alone to actually filter down our data. And then like I mentioned,
our data. And then like I mentioned, lesson 9 will be buttons where we'll
lesson 9 will be buttons where we'll actually build this out here and
actually build this out here and understanding how buttons work and also
understanding how buttons work and also bookmarks. Now, this report also
bookmarks. Now, this report also includes the two pages for our
includes the two pages for our dashboard. This is our first official
dashboard. This is our first official project dashboard that we're going to be
project dashboard that we're going to be building and it's on our data set and it
building and it's on our data set and it allows us to actually dive into if I
allows us to actually dive into if I want to dive into data engineers can
want to dive into data engineers can filter down for it and then it provides
filter down for it and then it provides a drill through. If I click this to get
a drill through. If I click this to get more in-depth data points for this
more in-depth data points for this particular topic of data engineer want
particular topic of data engineer want to navigate back I just click this back
to navigate back I just click this back arrow right here holding control
arrow right here holding control navigates me back to the dashboard.
navigates me back to the dashboard. We'll get to the dashboard when we get
We'll get to the dashboard when we get to the project session, but I wanted to
to the project session, but I wanted to warn you that's in this report because
warn you that's in this report because we're going to be using a lot of the
we're going to be using a lot of the visualizations that we build throughout
visualizations that we build throughout this chapter in this dashboard.
this chapter in this dashboard. Basically, we're not going to be wasting
Basically, we're not going to be wasting any of our work. Now, one quick note on
any of our work. Now, one quick note on the purpose of this chapter. This is not
the purpose of this chapter. This is not meant for us to go through and you to be
meant for us to go through and you to be a basic technical nerd about how to
a basic technical nerd about how to build each of these visuals, although we
build each of these visuals, although we will cover that. I feel the more
will cover that. I feel the more important part is understanding when you
important part is understanding when you should apply each of these visuals given
should apply each of these visuals given a certain problem you need to tackle. So
a certain problem you need to tackle. So yes, pay attention how they're built,
yes, pay attention how they're built, but more importantly, pay attention to
but more importantly, pay attention to when they are actually used.
So let's get into our first of four visualizations we're going to be
visualizations we're going to be building for this. And in this one, we
building for this. And in this one, we need to understand what the difference
need to understand what the difference is between a column and bar chart. For
is between a column and bar chart. For this, we're going to be asking this
this, we're going to be asking this question. What is the highest paying job
question. What is the highest paying job in data? And for this we only want to
in data? And for this we only want to look at remember our data set contains
look at remember our data set contains 10 distinct job titles. We just want to
10 distinct job titles. We just want to limit it to these uh six of basically
limit it to these uh six of basically data analysts, scientists, engineers,
data analysts, scientists, engineers, and also their senior roles. So for you,
and also their senior roles. So for you, let's start out in a brand new PowerBI
let's start out in a brand new PowerBI file. I'll select blank report. Peeking
file. I'll select blank report. Peeking in the data pane. There's no data in
in the data pane. There's no data in here. So let's import in our data set.
here. So let's import in our data set. Remember, it's a text CSV file. It's
Remember, it's a text CSV file. It's inside of our data folder and it's that
inside of our data folder and it's that job postings flat CSV. Everything's
job postings flat CSV. Everything's looking good with this navigator pop-up
looking good with this navigator pop-up that pops up and we'll load it in. Data
that pops up and we'll load it in. Data set completed, loaded in. Everything's
set completed, loaded in. Everything's looking well underneath this data pane.
looking well underneath this data pane. But like always, I want to go into table
But like always, I want to go into table view and just go through and make sure
view and just go through and make sure that everything is formatted correctly.
that everything is formatted correctly. Specifically, if you remember from last
Specifically, if you remember from last time, we had that salary year average.
time, we had that salary year average. If I sort it to sending, it's only right
If I sort it to sending, it's only right now a whole number. I'm going to change
now a whole number. I'm going to change this to a currency. And for the decimal
this to a currency. And for the decimal places, I'm going to change this to
places, I'm going to change this to zero. We're also going to update the
zero. We're also going to update the salary hour average to a currency as
salary hour average to a currency as well. And for this, we'll give it two
well. And for this, we'll give it two decimal places. As always with every
decimal places. As always with every file, we need to make sure that we're
file, we need to make sure that we're saving it often. So, I'm just going to
saving it often. So, I'm just going to save it here on my desktop. So, let's
save it here on my desktop. So, let's actually get into building this
actually get into building this visualization on our canvas. I'm going
visualization on our canvas. I'm going to go ahead and select stacked bar chart
to go ahead and select stacked bar chart to add it in. I'm going to resize it to
to add it in. I'm going to resize it to take up the top quarter. For this, we
take up the top quarter. For this, we want the job titles along the Y ais and
want the job titles along the Y ais and the count of them along along the X-
the count of them along along the X- axis. We can use both these fields for
axis. We can use both these fields for this. So, I'm going to drag job titles
this. So, I'm going to drag job titles short into both of these. From here, I'm
short into both of these. From here, I'm going to go into focus mode so we can
going to go into focus mode so we can drill into it closer. All right. Right.
drill into it closer. All right. Right. So, this is a bar chart. Bar charts go
So, this is a bar chart. Bar charts go horizontally. Let's compare this to a
horizontally. Let's compare this to a column chart. We'll use a the same
column chart. We'll use a the same format. Specifically, we'll use that
format. Specifically, we'll use that stacked column chart. And the column
stacked column chart. And the column charts go up and down. The way I
charts go up and down. The way I remember this is pretty easy. Columns
remember this is pretty easy. Columns like that of a building go up and down.
like that of a building go up and down. And the column chart does the same
And the column chart does the same thing, but we're building a bar chart
thing, but we're building a bar chart for this. So, we're going to change this
for this. So, we're going to change this back to a stacked bar chart. And
back to a stacked bar chart. And navigating back to our what our final
navigating back to our what our final visualization look like. I realize I
visualization look like. I realize I made a grave mistake. I didn't read this
made a grave mistake. I didn't read this fully. We're trying to plot or make a
fully. We're trying to plot or make a visualization of what is the highest
visualization of what is the highest paying job in data. We don't need to be
paying job in data. We don't need to be doing a count of jobs. We need to be
doing a count of jobs. We need to be doing the median salary of jobs. So
doing the median salary of jobs. So let's actually update this visual. I'm
let's actually update this visual. I'm going to take that salary year average
going to take that salary year average column and I'm going to drag it into the
column and I'm going to drag it into the xaxis. Right now we have a sum of the
xaxis. Right now we have a sum of the salary year average. We want to actually
salary year average. We want to actually change that to a median. And right now
change that to a median. And right now it's a right stack bar chart. So that we
it's a right stack bar chart. So that we have multiple different values going
have multiple different values going here. We don't want that count of job
here. We don't want that count of job tiles short. So I'm going to go ahead
tiles short. So I'm going to go ahead and click that to exit out. All right.
and click that to exit out. All right. Navigating back to the canvas area
Navigating back to the canvas area itself. I want to put a title first
itself. I want to put a title first because that influences my decision on
because that influences my decision on how I'm going to format the rest of the
how I'm going to format the rest of the chart. If we want to format the visuals
chart. If we want to format the visuals title, remember we can't we have to be
title, remember we can't we have to be selected on the visual. If I were to
selected on the visual. If I were to click this, it's not going to give us
click this, it's not going to give us what we want. So, actually select the
what we want. So, actually select the visual, select format your visual. And
visual, select format your visual. And then underneath the general selection,
then underneath the general selection, that's where the title is. We're going
that's where the title is. We're going to change this to what is the highest
to change this to what is the highest paying job in data. I'm going to give
paying job in data. I'm going to give this a size 20 point font. and also
this a size 20 point font. and also we're going to center it. I like to
we're going to center it. I like to typically ask a question with my charts
typically ask a question with my charts to guide the user or the end user on
to guide the user or the end user on what they should be looking for in the
what they should be looking for in the visual. Going back into focus mode,
visual. Going back into focus mode, understanding what this title is, we can
understanding what this title is, we can see that this is clearly job titles. So,
see that this is clearly job titles. So, I don't need a y-axis label. So, under
I don't need a y-axis label. So, under format your visual under the visual
format your visual under the visual section, I can go into y-axis. And we
section, I can go into y-axis. And we don't want to toggle on or off the
don't want to toggle on or off the values, but instead we want to toggle
values, but instead we want to toggle off the uh the title itself. Next, let's
off the uh the title itself. Next, let's format the Xaxis label. We could do that
format the Xaxis label. We could do that here underneath the title section. You
here underneath the title section. You can update it right here. It's auto
can update it right here. It's auto right now. I don't recommend doing it
right now. I don't recommend doing it here. Instead, we're going to double
here. Instead, we're going to double click the field well. And then we'll
click the field well. And then we'll replace this value here with the value
replace this value here with the value of median yearly salary. And then
of median yearly salary. And then typically, I like to provide what are
typically, I like to provide what are the units of currency. In this case,
the units of currency. In this case, it's USD. So, not bad. If I scroll over
it's USD. So, not bad. If I scroll over this visual, we can see that data
this visual, we can see that data scientists are getting paid $155,000.
scientists are getting paid $155,000. Notice that that it says job title short
Notice that that it says job title short in front of that. Because of that, I'm
in front of that. Because of that, I'm going to also update this y-axis right
going to also update this y-axis right here to say job title. So now whenever I
here to say job title. So now whenever I scroll over the tool tip, it looks a lot
scroll over the tool tip, it looks a lot cleaner. So let's get into filtering
cleaner. So let's get into filtering these values down. Remember, we want
these values down. Remember, we want data analyst, data scientist, data
data analyst, data scientist, data engineers, and also their senior roles.
engineers, and also their senior roles. The common thing about them all is they
The common thing about them all is they contain the word data. So, opening up
contain the word data. So, opening up the filters pane and underneath filters
the filters pane and underneath filters on this visual, we want to filter the
on this visual, we want to filter the job title. Now, I could go through and
job title. Now, I could go through and select those six, but I'm lazy, so I'm
select those six, but I'm lazy, so I'm actually going to go into advanced
actually going to go into advanced filtering. And it says, hey, we can show
filtering. And it says, hey, we can show the items when the value contains, in
the items when the value contains, in our case, we want it to contain the word
our case, we want it to contain the word data. Apply the filter. Bam, we get
data. Apply the filter. Bam, we get those six roles. All right, so now we
those six roles. All right, so now we can actually sit back and analyze it. We
can actually sit back and analyze it. We see that senior roles are typically paid
see that senior roles are typically paid higher except in the case of senior data
higher except in the case of senior data analyst. Little questionable there. I
analyst. Little questionable there. I don't know what's going on, but overall
don't know what's going on, but overall all these median salaries are where I
all these median salaries are where I expect. Also, quick note, we're going to
expect. Also, quick note, we're going to be doing or focusing on median values
be doing or focusing on median values throughout this entire course over
throughout this entire course over something like average. If I go to that
something like average. If I go to that table view and sort so uh salary year
table view and sort so uh salary year average in descending order, you can see
average in descending order, you can see we have a lot of high values here. In
we have a lot of high values here. In this case, we have one job that has
this case, we have one job that has $920,000
$920,000 as a salary. If we were to use average,
as a salary. If we were to use average, it's going to distort this value that
it's going to distort this value that we're going to seeing. It's going to
we're going to seeing. It's going to make it much higher than what we'd
make it much higher than what we'd expect. That's why we're using median
expect. That's why we're using median because it more or less normalizes what
because it more or less normalizes what we should see for the salary. And as
we should see for the salary. And as proof of this, I can just show you
proof of this, I can just show you senior data scientists are at 155,000
senior data scientists are at 155,000 for their median salary. If I were to
for their median salary. If I were to change this to average, they go up to
change this to average, they go up to 155,900.
155,900. And I don't know if you noticed, but all
And I don't know if you noticed, but all the other ones also increased. So, it's
the other ones also increased. So, it's really unrealistic for us to display
really unrealistic for us to display these average values. That's why we're
these average values. That's why we're going to do median because that's more
going to do median because that's more realistic of what you would expect to
realistic of what you would expect to see if you were applying for these jobs.
Next question to get into relates on these lines and that is what is the
these lines and that is what is the highest paying job globally. So similar
highest paying job globally. So similar before we're going to be looking at
before we're going to be looking at those same six job titles but for this
those same six job titles but for this we're going to be looking at the top
we're going to be looking at the top four countries or the four countries
four countries or the four countries that have the most amount of jobs. So
that have the most amount of jobs. So back in our canvas I don't like starting
back in our canvas I don't like starting from scratch if I don't need to. So I'm
from scratch if I don't need to. So I'm actually going to copy this visual by
actually going to copy this visual by pressing Ctrl + C. Make sure that it's
pressing Ctrl + C. Make sure that it's actually selected and then press Ctrl +V
actually selected and then press Ctrl +V to copy it down and paste it. I'm going
to copy it down and paste it. I'm going paste it underneath. I'm going to update
paste it underneath. I'm going to update the title to what is the highest paying
the title to what is the highest paying job globally so we don't have a repeat
job globally so we don't have a repeat of last time me doing the aggregation in
of last time me doing the aggregation in the wrong column. So with this, let's
the wrong column. So with this, let's change this into the correct chart type
change this into the correct chart type that we want to use. We want to use this
that we want to use. We want to use this clustered column chart. And if you
clustered column chart. And if you notice, it went through and actually
notice, it went through and actually swapped that x-axis and y-axis to make
swapped that x-axis and y-axis to make sure the values right. Unfortunately, it
sure the values right. Unfortunately, it didn't keep our label. So, I'm going to
didn't keep our label. So, I'm going to go ahead and update that. All right. So,
go ahead and update that. All right. So, remember we want this with the country
remember we want this with the country along the x-axis and basically have the
along the x-axis and basically have the different job titles aggregated in
different job titles aggregated in between it. So, navigating to our visual
between it. So, navigating to our visual going into focus mode. I'm going to take
going into focus mode. I'm going to take job country and let's just drag it into
job country and let's just drag it into the x-axis. Now, if you go through this,
the x-axis. Now, if you go through this, we can actually see that it combines
we can actually see that it combines every job title and also job country.
every job title and also job country. So, in this case, this is in Armenia.
So, in this case, this is in Armenia. This is for data analysts and this is
This is for data analysts and this is their median salary. This is basically
their median salary. This is basically highly unreadable and highly unusable.
highly unreadable and highly unusable. What we actually want to do is we want
What we actually want to do is we want the job we want to keep job country on
the job we want to keep job country on that x-axis, but we're going to take the
that x-axis, but we're going to take the job title and we're going to drag it on
job title and we're going to drag it on down. Specifically, I want to take this
down. Specifically, I want to take this down into legend. And bam, there's what
down into legend. And bam, there's what we want. Although also highly unreadable
we want. Although also highly unreadable because we have close almost 200
because we have close almost 200 countries. There's too many countries on
countries. There's too many countries on here to actually use. So for this
here to actually use. So for this visual, we need to apply a filter on it
visual, we need to apply a filter on it based on so filter on this visual in the
based on so filter on this visual in the job country column. Now we could filter
job country column. Now we could filter I could scroll through this and see the
I could scroll through this and see the different counts and select the ones
different counts and select the ones that I want. But you know I'm lazy. I
that I want. But you know I'm lazy. I like to automate it. So we're going to
like to automate it. So we're going to instead use the filter type and we're
instead use the filter type and we're going to change this now to use top N.
going to change this now to use top N. Specifically want the top four
Specifically want the top four countries. But what do we want the top
countries. But what do we want the top four countries based on? Well, we want
four countries based on? Well, we want them based on the count of those
them based on the count of those countries. So, I'll change this to count
countries. So, I'll change this to count from first and then I'll click apply
from first and then I'll click apply filter. And there we have it. United
filter. And there we have it. United Kingdom, United States, France, and also
Kingdom, United States, France, and also India in there. Now, there's a lot of
India in there. Now, there's a lot of different data points going on in here.
different data points going on in here. And I'm noticing right now too with it
And I'm noticing right now too with it that this x-axis I need to update it to
that this x-axis I need to update it to just country so that way it's more
just country so that way it's more readable. But there's a lot of different
readable. But there's a lot of different data points in here to actually view. If
data points in here to actually view. If for some reason you wanted to get those
for some reason you wanted to get those data points or maybe somebody else did,
data points or maybe somebody else did, you click the three dots up the top
you click the three dots up the top right hand corner and then you could go
right hand corner and then you could go here to show as table and then you have
here to show as table and then you have all these different values here and you
all these different values here and you can actually see them more visually here
can actually see them more visually here if you wanted to. Also, you could just
if you wanted to. Also, you could just export the data as well and it's going
export the data as well and it's going to exported it out. All right, so let's
to exported it out. All right, so let's go back to our report. I want to clean
go back to our report. I want to clean up one thing real quick. If we look at
up one thing real quick. If we look at that filters tab, remember we have job
that filters tab, remember we have job titles contains data right here on this
titles contains data right here on this visual and also right here on this
visual and also right here on this visual. I actually want to apply it to
visual. I actually want to apply it to the entire page. So what I'm going to do
the entire page. So what I'm going to do is I'm going to just take this and I'm
is I'm going to just take this and I'm going to drag it into filters on this
going to drag it into filters on this page. And as you notice, it's not
page. And as you notice, it's not actually working. So instead, what I'm
actually working. So instead, what I'm going to do is I'm going to drag job
going to do is I'm going to drag job tile short onto here. Do that advanced
tile short onto here. Do that advanced filtering for those jobs that contain
filtering for those jobs that contain data. and then click apply filter. Now
data. and then click apply filter. Now for each one of these uh visuals, we
for each one of these uh visuals, we don't need to maintain it on here long.
don't need to maintain it on here long. It's just sort of redundant. I'll remove
It's just sort of redundant. I'll remove it on this visual. Selecting this
it on this visual. Selecting this visual, I'll also remove it by se
visual, I'll also remove it by se selecting clear filter. So now it's
selecting clear filter. So now it's removed on both of these, but it's
removed on both of these, but it's applied when I click the page. It's
applied when I click the page. It's applied on the page. Also, sometimes
applied on the page. Also, sometimes whenever you just click onto here, it's
whenever you just click onto here, it's going to generate these other visuals.
going to generate these other visuals. It's sort of annoying. Anytime you need
It's sort of annoying. Anytime you need to remove them, you just click those
to remove them, you just click those ellipses and click remove. All right.
ellipses and click remove. All right. So, this, as a reminder, is a clustered
So, this, as a reminder, is a clustered column or if I wanted to, I could change
column or if I wanted to, I could change it to a clustered bar chart.
All right. Next up is a stacked column, or if you will, stacked bar chart. We're
or if you will, stacked bar chart. We're going to make it into a stack column
going to make it into a stack column chart. With this visualization, we want
chart. With this visualization, we want to see not only what are the counts of
to see not only what are the counts of the different job titles, but we want to
the different job titles, but we want to see the breakdown of whether they
see the breakdown of whether they mention a degree requirement in the job
mention a degree requirement in the job posting. If we go into our table view,
posting. If we go into our table view, we have this column here on job no
we have this column here on job no degree mention. It's a true or false
degree mention. It's a true or false value. If it's true, there's no mention
value. If it's true, there's no mention of a degree requirement in the job
of a degree requirement in the job posting. Doesn't mean that doesn't
posting. Doesn't mean that doesn't require a degree. it just means that
require a degree. it just means that they don't mention it. So, in the case
they don't mention it. So, in the case of it being false, there is a degree
of it being false, there is a degree requirement mentioned in the job
requirement mentioned in the job posting. Anyway, let's actually
posting. Anyway, let's actually visualize this for those top six jobs. I
visualize this for those top six jobs. I don't like starting from scratch, so I'm
don't like starting from scratch, so I'm going to copy this first visual, press
going to copy this first visual, press commandV, drag it over to the top right
commandV, drag it over to the top right hand corner. Personally, I like whenever
hand corner. Personally, I like whenever we have these labels here uh going into
we have these labels here uh going into f mode written in this manner and so
f mode written in this manner and so keeping it as a bar chart. But like I
keeping it as a bar chart. But like I said, we're going to be using a stacked
said, we're going to be using a stacked column chart for this instead. Right
column chart for this instead. Right now, we're doing the median salary, but
now, we're doing the median salary, but we need a count of the job titles. So,
we need a count of the job titles. So, I'll drag the job title short into that
I'll drag the job title short into that y-axis. Click that median off here. Now,
y-axis. Click that median off here. Now, we have the count, but we want to see
we have the count, but we want to see the breakdown of job no degree mention.
the breakdown of job no degree mention. So what we can do with this is throw
So what we can do with this is throw this into the legend. So taking job no
this into the legend. So taking job no degree mention put it there. And now
degree mention put it there. And now these values are stacked. We're going to
these values are stacked. We're going to do some clean up of the columns.
do some clean up of the columns. Changing y-axis to job title. Changing
Changing y-axis to job title. Changing the legend to no degree mentioned. And
the legend to no degree mentioned. And then lastly changing that title. So
then lastly changing that title. So under format your visual under general
under format your visual under general under title we change it to what are the
under title we change it to what are the top jobs with no degree mentioned. And
top jobs with no degree mentioned. And looking at it, data engineers by far
looking at it, data engineers by far have some of the the highest amounts of
have some of the the highest amounts of jobs that have no degree mentioned in
jobs that have no degree mentioned in the job posting, but data analysts
the job posting, but data analysts aren't far behind.
Last visual to make is a 100% stacked column or bar chart. In this case, we're
column or bar chart. In this case, we're looking at obviously a bar chart. Now,
looking at obviously a bar chart. Now, this is great anytime you want to
this is great anytime you want to visualize proportions like in our last
visualize proportions like in our last case. Yeah, it's great that we can see
case. Yeah, it's great that we can see what is the overall quantity values, but
what is the overall quantity values, but say we are stuck in something like
say we are stuck in something like senior data engineers, senior data
senior data engineers, senior data scientists, we may want to better
scientists, we may want to better understand what are the proportions of
understand what are the proportions of jobs that this is likely to happen. In
jobs that this is likely to happen. In that case, we could build a
that case, we could build a visualization like this that shows what
visualization like this that shows what portions of jobs mention a degree. In
portions of jobs mention a degree. In this case, we could use something like a
this case, we could use something like a 100% stacked bar column chart to
100% stacked bar column chart to visualize this proportion to see what
visualize this proportion to see what portion of JSP should agree. So, let's
portion of JSP should agree. So, let's build this bad boy. So, a lot of the
build this bad boy. So, a lot of the stuff is going to be using this visual
stuff is going to be using this visual right here. I'm going to go ahead and
right here. I'm going to go ahead and copy it and paste it. And then come up
copy it and paste it. And then come up here and change this into a 100% stacked
here and change this into a 100% stacked bar chart. Moving this into focus mode.
bar chart. Moving this into focus mode. We pretty much have this completely
We pretty much have this completely built. We just got to update a few
built. We just got to update a few titles and update it to what portion of
titles and update it to what portion of top jobs have no degree mentioned. And
top jobs have no degree mentioned. And the only other thing to clean up on this
the only other thing to clean up on this is the actual x-axis title. I'll do that
is the actual x-axis title. I'll do that from here. And we'll change this to job
from here. And we'll change this to job count. So with this, although we did see
count. So with this, although we did see from last time that data analysts and
from last time that data analysts and data engineers had some of the highest
data engineers had some of the highest quantities, when we actually look at the
quantities, when we actually look at the 100% stack view, we can see that things
100% stack view, we can see that things like senior data engineers and data
like senior data engineers and data engineers are both pretty much it's like
engineers are both pretty much it's like half the postings don't have a
half the postings don't have a requirement or don't mention a
requirement or don't mention a requirement of a degree. And data
requirement of a degree. And data analysts correlate as well. They're
analysts correlate as well. They're around 40%. and then sat uh data
around 40%. and then sat uh data scientists apparently pretty stingy.
scientists apparently pretty stingy. Seven almost 7% on both have a no
Seven almost 7% on both have a no mention of a degree whereas like 93
mention of a degree whereas like 93 require some sort of degree. So if you
require some sort of degree. So if you don't have a degree, if you're not
don't have a degree, if you're not focused on data analyst jobs, you should
focused on data analyst jobs, you should also be focusing on data engineer jobs.
also be focusing on data engineer jobs. All right, so boom, that is the
All right, so boom, that is the different column and bar charts. They're
different column and bar charts. They're all along the top line here. The last
all along the top line here. The last thing I'm going to do on this is just
thing I'm going to do on this is just update this page title to be called
update this page title to be called column and bar and then make sure you
column and bar and then make sure you save it. We now have some practice
save it. We now have some practice problems for you to go through and get
problems for you to go through and get more familiar with when you should be
more familiar with when you should be using bar and also column charts and
using bar and also column charts and these different aggregation or
these different aggregation or variations of them each. In the next
variations of them each. In the next lesson, we're going to be going into
lesson, we're going to be going into line and area charts. With that, I'll
line and area charts. With that, I'll see you there.
Welcome to this lesson on line and area charts. And after things like bar and
charts. And after things like bar and column charts, which we covered in the
column charts, which we covered in the previous lesson, this is the second most
previous lesson, this is the second most common type of charts that I find myself
common type of charts that I find myself using. Let's jump into the final report
using. Let's jump into the final report to see what we're going to be building
to see what we're going to be building in this lesson. First, we're going to
in this lesson. First, we're going to start simple, building a simple line
start simple, building a simple line chart, understanding what is the trend
chart, understanding what is the trend of jobs in 2024. Remember, this data set
of jobs in 2024. Remember, this data set that we're working with only includes
that we're working with only includes jobs from 2024. Next, we'll transition
jobs from 2024. Next, we'll transition this over into an area chart, which if
this over into an area chart, which if you see, it has a similar trend that our
you see, it has a similar trend that our line chart did, but in this case, we're
line chart did, but in this case, we're able to now see what are the different
able to now see what are the different jobs that compromise or compose those
jobs that compromise or compose those different job counts. And anytime you
different job counts. And anytime you have any type of stacked area chart, you
have any type of stacked area chart, you have probably some sort of 100% stacked
have probably some sort of 100% stacked area chart. Finally, we'll wrap it up
area chart. Finally, we'll wrap it up with this visualization looking how we
with this visualization looking how we can combine column charts with also line
can combine column charts with also line charts. In this case, we're going to be
charts. In this case, we're going to be comparing what is the yearly median
comparing what is the yearly median salary compared to hourly median salary
salary compared to hourly median salary of those top 10 jobs.
So, let's get into building this bad boy of understanding what is the trend of
of understanding what is the trend of jobs in 2024. In the PowerB report we've
jobs in 2024. In the PowerB report we've been working on, I'm going to create a
been working on, I'm going to create a new page and I'm going to change the
new page and I'm going to change the title of this to line and area. Clicking
title of this to line and area. Clicking inside the canvas, I'm going to insert
inside the canvas, I'm going to insert in a line chart. We'll drag this into
in a line chart. We'll drag this into the top quadrant. So along the bottom
the top quadrant. So along the bottom along the x-axis, we want to use the job
along the x-axis, we want to use the job posted date column. We're going to dive
posted date column. We're going to dive into this a little bit more. Right now,
into this a little bit more. Right now, nothing's appearing. We need to put
nothing's appearing. We need to put something into the yaxis. Specifically,
something into the yaxis. Specifically, want the counts of jobs. Remember, we're
want the counts of jobs. Remember, we're going to just use that job title short
going to just use that job title short column because we don't have necessarily
column because we don't have necessarily a job ID column. This is going to be
a job ID column. This is going to be good enough. Okay. We can see from our
good enough. Okay. We can see from our visualization right now that if I hover
visualization right now that if I hover over it, it's only showing one data
over it, it's only showing one data point and it's a dot. It's not even a
point and it's a dot. It's not even a line. because it's only showing this for
line. because it's only showing this for the year of 2024. If I wanted to, I can
the year of 2024. If I wanted to, I can navigate down. We're going to dive in
navigate down. We're going to dive in more into drill downs right after this,
more into drill downs right after this, but mainly I just show you that we will
but mainly I just show you that we will be able to navigate into all the
be able to navigate into all the different job titles depending on what
different job titles depending on what we want. The main thing to understand is
we want. The main thing to understand is that for this x-axis, I'm going to
that for this x-axis, I'm going to actually close it out. Remember when we
actually close it out. Remember when we drag this job posted date over, it put
drag this job posted date over, it put this date hierarchy which is over here
this date hierarchy which is over here in the column. So I can actually open
in the column. So I can actually open this up and similarly it has year
this up and similarly it has year quarter month day. Here I have year
quarter month day. Here I have year quarter month day. For the time being
quarter month day. For the time being all we're going to do before we get into
all we're going to do before we get into covering that this drill down
covering that this drill down functionality that's highly complex I
functionality that's highly complex I feel. We're going to just remove these
feel. We're going to just remove these other fields of year, quarter, and then
other fields of year, quarter, and then also day. And we're just going to keep
also day. And we're just going to keep the month for right now. I'm going to
the month for right now. I'm going to open it up into focus mode. We're going
open it up into focus mode. We're going to build out this line chart to make
to build out this line chart to make sure that it has everything right and
sure that it has everything right and correct in it. And then we're going to
correct in it. And then we're going to jump into drill down using those arrows
jump into drill down using those arrows to navigate up and down in this. First
to navigate up and down in this. First thing I'm going to change is the title.
thing I'm going to change is the title. Going to format your visual under
Going to format your visual under general to title. I only have jobs in
general to title. I only have jobs in 2024. So we'll call this what is trend
2024. So we'll call this what is trend of jobs in 2024. The x-axis label is a
of jobs in 2024. The x-axis label is a little redundant because we're already
little redundant because we're already saying that hey we're looking at dates.
saying that hey we're looking at dates. So I'm going to turn off the title. Then
So I'm going to turn off the title. Then for the yaxis label I'm going to change
for the yaxis label I'm going to change this to instead be something more
this to instead be something more readable of job count. All right. So
readable of job count. All right. So this is looking good. We have everything
this is looking good. We have everything formatted as we wanted. If we remember,
formatted as we wanted. If we remember, we had a trend line previously. How do
we had a trend line previously. How do we add something like a trend line?
we add something like a trend line? Well, previously we've looked at this
Well, previously we've looked at this build visual. We've looked at this
build visual. We've looked at this format visual. And now we're going to
format visual. And now we're going to look at this analytics underneath the
look at this analytics underneath the visualization pane. Now, this is really
visualization pane. Now, this is really great anytime you want to add any kind
great anytime you want to add any kind of reference lines in here. such as if I
of reference lines in here. such as if I wanted a minimum line, I could come in
wanted a minimum line, I could come in here under minline, select add line, and
here under minline, select add line, and it adds this line in. Scrolling on down,
it adds this line in. Scrolling on down, I can even go into and turn on the data
I can even go into and turn on the data label. It's positioned on the left hand
label. It's positioned on the left hand side. It's above it. And what we want to
side. It's above it. And what we want to show, you could do data value name, or
show, you could do data value name, or in my case, I'd probably like something
in my case, I'd probably like something like min. Not too bad. I would dress it
like min. Not too bad. I would dress it up a little bit. I don't really like the
up a little bit. I don't really like the name of min one, so I'm going to edit it
name of min one, so I'm going to edit it and change that to minimum job count.
and change that to minimum job count. Now, I could also do the same and add an
Now, I could also do the same and add an average line as I've done here and also
average line as I've done here and also change the name. The formatting isn't
change the name. The formatting isn't necessarily correct. So, I could change
necessarily correct. So, I could change the value decimal places to just do zero
the value decimal places to just do zero and much more readable. But if we jump
and much more readable. But if we jump forward to what we're going to be
forward to what we're going to be building finally, I had on here a trend
building finally, I had on here a trend line yet it's not visible. If we
line yet it's not visible. If we actually go through our navigation menu,
actually go through our navigation menu, specifically coming back here and
specifically coming back here and looking under at further analysis,
looking under at further analysis, there's nothing for trend line.
there's nothing for trend line. Unfortunately, whenever we just drag one
Unfortunately, whenever we just drag one of these column values over under date
of these column values over under date hierarchy doesn't and it doesn't no
hierarchy doesn't and it doesn't no longer provides the opportunity to
longer provides the opportunity to provide this trend line. So, we'll add
provide this trend line. So, we'll add it later. For the time being, I'm going
it later. For the time being, I'm going to remove this average line and then I'm
to remove this average line and then I'm also going to remove this min line. I
also going to remove this min line. I don't want to bother.
So, let's get into understanding drill down. I'm going to go ahead and we're
down. I'm going to go ahead and we're going to go ahead and add all these
going to go ahead and add all these column values back. Now you notice as I
column values back. Now you notice as I added all these back, one these arrows
added all these back, one these arrows appeared and then two if I actually go
appeared and then two if I actually go into this add further analysis trend
into this add further analysis trend line appears now and I can click on I
line appears now and I can click on I can actually get a trend line. I can
can actually get a trend line. I can also change the formatting here into a
also change the formatting here into a light blue color. Anyway, I digress.
light blue color. Anyway, I digress. Let's get back into drill down. So of
Let's get back into drill down. So of all these, the easiest one is drill up.
all these, the easiest one is drill up. Right now I'm down in day. I can just
Right now I'm down in day. I can just click up and navigate all the way back
click up and navigate all the way back up to that year. I'm also going to
up to that year. I'm also going to navigate back here. The first down hour
navigate back here. The first down hour is to click to turn on drill down mode.
is to click to turn on drill down mode. It's going to be highlighted black. And
It's going to be highlighted black. And in this case, I can click on points on
in this case, I can click on points on the chart and then drill down into it.
the chart and then drill down into it. In that case, I drilled into 2024. And
In that case, I drilled into 2024. And now, if I wanted to drill into quarter
now, if I wanted to drill into quarter 2, I can click that. Then, if I want to
2, I can click that. Then, if I want to drill into May, I could do that. If I
drill into May, I could do that. If I wanted to drill further into May 13th,
wanted to drill further into May 13th, can't do that because that's as far as
can't do that because that's as far as low down as we can go. If I wanted to go
low down as we can go. If I wanted to go back up, I just click back up. And at
back up, I just click back up. And at any point I can turn off this drill mode
any point I can turn off this drill mode by clicking on the drill mode and then
by clicking on the drill mode and then just navigating where I want to. The
just navigating where I want to. The next one is to go to the next level in
next one is to go to the next level in the hierarchy. So as expected this we're
the hierarchy. So as expected this we're going to click on it. We actually do
going to click on it. We actually do navigate down. In this case we're
navigate down. In this case we're getting quarter 1, quarter 2, quarter 3,
getting quarter 1, quarter 2, quarter 3, quarter 4. I'll click down again, get
quarter 4. I'll click down again, get the months. But I click down one more
the months. But I click down one more time and we see that it's a list of
time and we see that it's a list of numbers for month numbers. This double
numbers for month numbers. This double down arrow would be used in cases where
down arrow would be used in cases where you have multiple years and maybe you
you have multiple years and maybe you wanted to look at something like every
wanted to look at something like every single August or every single September.
single August or every single September. In our case, we only have one year of
In our case, we only have one year of 2024. And so that's why when we drill
2024. And so that's why when we drill all the way down to this, we're getting
all the way down to this, we're getting these following values, which
these following values, which technically this puts together for this
technically this puts together for this case, if we were looking at the second,
case, if we were looking at the second, this puts together January through
this puts together January through December, the counts on the 2nd. And
December, the counts on the 2nd. And then something like the 31st is super
then something like the 31st is super low at like 9,000 because 31st only
low at like 9,000 because 31st only happens one, two, three, like six times
happens one, two, three, like six times in a year. Actually, I think it's seven.
in a year. Actually, I think it's seven. Anyway, I bring that up because
Anyway, I bring that up because typically you actually don't want that.
typically you actually don't want that. Anytime I'm navigating to something like
Anytime I'm navigating to something like this, the down arrow that I want to use
this, the down arrow that I want to use is this expand all down one level in the
is this expand all down one level in the hierarchy. I'm going to go down and
hierarchy. I'm going to go down and notice with this one, it's actually has
notice with this one, it's actually has the year next to it. If we go back up,
the year next to it. If we go back up, go down. This one says just quarter 1,
go down. This one says just quarter 1, quarter 2. So, we know that we're
quarter 2. So, we know that we're navigating down in the hierarchy fully.
navigating down in the hierarchy fully. So we have each of these which is still
So we have each of these which is still quarterly and then we get into monthly
quarterly and then we get into monthly for that year and then we see
for that year and then we see everybody's dailies across the entire
everybody's dailies across the entire year. Our data has a lot of seasonality
year. Our data has a lot of seasonality to this. Specifically, if you were to
to this. Specifically, if you were to count each one of these ups and downs,
count each one of these ups and downs, you count 52 for 52 weeks in a year.
you count 52 for 52 weeks in a year. These low points are typically on the
These low points are typically on the weekend, usually Saturday and Sunday,
weekend, usually Saturday and Sunday, because that's when job postings are not
because that's when job postings are not getting uploaded because people aren't
getting uploaded because people aren't applying to jobs. Then the high points
applying to jobs. Then the high points are during the week. Anyway, this in my
are during the week. Anyway, this in my opinion is not very readable. So, I'm
opinion is not very readable. So, I'm going to drill up one level and we'll
going to drill up one level and we'll keep it in this monthly. So, one last
keep it in this monthly. So, one last note on this. I just went through over
note on this. I just went through over the last couple minutes explaining this
the last couple minutes explaining this drill down functionality to you cuz it's
drill down functionality to you cuz it's not that intuitive. Anytime you're
not that intuitive. Anytime you're building any type of report, it's good
building any type of report, it's good practice to put it and then save it on
practice to put it and then save it on what it is you want them to view because
what it is you want them to view because they're most likely not going to
they're most likely not going to understand how to do the drill down and
understand how to do the drill down and drill up unless you teach them how to
drill up unless you teach them how to use it.
Next visual we're going to get into building is a stacked area chart. Now,
building is a stacked area chart. Now, they do have an option for an area
they do have an option for an area chart, and if there's only a couple
chart, and if there's only a couple values, maybe okay with it. I'm
values, maybe okay with it. I'm typically always going to recommend
typically always going to recommend stacked area chart. Anyway, for this, we
stacked area chart. Anyway, for this, we want to see what is the trend of data
want to see what is the trend of data jobs. Basically, we're showing what we
jobs. Basically, we're showing what we had previously, but we're breaking it
had previously, but we're breaking it down further in the legend by job title.
down further in the legend by job title. All right, so for this, the easiest
All right, so for this, the easiest thing is let's just actually copyr C and
thing is let's just actually copyr C and Crl + V and build on this previous line
Crl + V and build on this previous line chart that we have. And I'm going to
chart that we have. And I'm going to just convert this into a stacked area
just convert this into a stacked area chart. I'm going to change the title
chart. I'm going to change the title real quick to make sure that we're
real quick to make sure that we're staying on task to what is the trend of
staying on task to what is the trend of data jobs in 2024. Remember, I like the
data jobs in 2024. Remember, I like the title a little bit bigger than this. I'm
title a little bit bigger than this. I'm going put a 20oint font. I'm also going
going put a 20oint font. I'm also going to center it. If I select this previous
to center it. If I select this previous visual, it still has this open so I can
visual, it still has this open so I can thus update the title as well for it.
thus update the title as well for it. Putting it as 20 point font in the
Putting it as 20 point font in the center. Anyway, back to this one.
center. Anyway, back to this one. Entering it into focus mode. Navigating
Entering it into focus mode. Navigating back to build visual. Remember, we want
back to build visual. Remember, we want to break this down by job titles. So,
to break this down by job titles. So, I'm going to drag that job title short
I'm going to drag that job title short into the legend. And then I'm going to
into the legend. And then I'm going to change that legend to job title just to
change that legend to job title just to show that point that we're trying to
show that point that we're trying to make. Right? This is a stacked area
make. Right? This is a stacked area chart. And this is going up to the
chart. And this is going up to the values of almost 55,000 here. If we were
values of almost 55,000 here. If we were to do just an area chart, it causes it
to do just an area chart, it causes it to overlap and then the values go down.
to overlap and then the values go down. This is just very
This is just very I'm just like I'm having a meltdown
I'm just like I'm having a meltdown right now. does not show anything useful
right now. does not show anything useful out of it. Stacked area chart already is
out of it. Stacked area chart already is a little hard to read. That makes it
a little hard to read. That makes it even harder to read. Similarly, with
even harder to read. Similarly, with this one, we can drill down in the
this one, we can drill down in the hierarchy. If I wanted to go to a daily
hierarchy. If I wanted to go to a daily basis, oh my gosh, I'm going need to
basis, oh my gosh, I'm going need to take some aspirin for this. Going back
take some aspirin for this. Going back up, could navigate into the quarters or
up, could navigate into the quarters or fully for the year. We're going to put
fully for the year. We're going to put that back down into monthly. One thing
that back down into monthly. One thing that you may want to add to a line chart
that you may want to add to a line chart or an area chart that has values that
or an area chart that has values that you may want to control is this. So
you may want to control is this. So underneath visuals and format your
underneath visuals and format your visual, they have this zoom slider. I'm
visual, they have this zoom slider. I'm going to go ahead and turn it on. It
going to go ahead and turn it on. It automatically enables it for the X and
automatically enables it for the X and Yaxis. In this case, that allows the
Yaxis. In this case, that allows the user to go in and zoom in on a
user to go in and zoom in on a particular area for what they want to
particular area for what they want to do. So if they wanted to drill down into
do. So if they wanted to drill down into the daily portion, they could and then
the daily portion, they could and then look at, hey, what's going on during
look at, hey, what's going on during this week right here, I can also enable
this week right here, I can also enable depending on what I want, if the x-axis
depending on what I want, if the x-axis or y-axis, and typically I would just do
or y-axis, and typically I would just do it on the x-axis, especially if it has
it on the x-axis, especially if it has date values. Navigate back up to month.
Anytime we have any type of stacked visualization, remember we can do
visualization, remember we can do something like a 100% stacked
something like a 100% stacked visualization. In this case, 100%
visualization. In this case, 100% stacked area chart. This is the same
stacked area chart. This is the same data that we did previously, but just
data that we did previously, but just put into a graph in order to analyze it
put into a graph in order to analyze it in a 100% format. Because of that, I'm
in a 100% format. Because of that, I'm just going to take that top chart up
just going to take that top chart up here, control C it, control + V, move
here, control C it, control + V, move into the bottom quadrant, put it into
into the bottom quadrant, put it into focus mode. As always, start with the
focus mode. As always, start with the title to what are the portion of data
title to what are the portion of data jobs in 2024. And then for the visual
jobs in 2024. And then for the visual itself, I'll change this into a 100%
itself, I'll change this into a 100% stacked area chart. And bam. One thing I
stacked area chart. And bam. One thing I will note, this job count, anytime we
will note, this job count, anytime we did a percentage, I didn't do it in the
did a percentage, I didn't do it in the last lesson, I probably should have, is
last lesson, I probably should have, is I would probably annotate that it is a
I would probably annotate that it is a percentage by updating this value here.
percentage by updating this value here. So now with this one, I feel we can read
So now with this one, I feel we can read it a at least a little bit better than
it a at least a little bit better than just the area chart. We can see towards
just the area chart. We can see towards the end of the year, data analyst
the end of the year, data analyst actually go up in their proportion and
actually go up in their proportion and they have around 30% of postings towards
they have around 30% of postings towards the end of the year. Pretty neat.
All right, last visualization to build and that is a line and column chart.
and that is a line and column chart. This one we're going to be looking at
This one we're going to be looking at yearly and also hourly median salary for
yearly and also hourly median salary for each of the 10 jobs that we have in the
each of the 10 jobs that we have in the job title short column. Personally, I
job title short column. Personally, I feel the yearly salary is more important
feel the yearly salary is more important in this case. So, we're going to make it
in this case. So, we're going to make it the columns because they really stand
the columns because they really stand out to me. And then from there, we'll
out to me. And then from there, we'll make the hourly the line. And
make the hourly the line. And personally, I don't like starting from
personally, I don't like starting from scratch if I don't need to. So, I'm
scratch if I don't need to. So, I'm going to grab this where's the highest
going to grab this where's the highest paying job in data visualization we made
paying job in data visualization we made on the other page. Copy it and then
on the other page. Copy it and then paste it on in here. Drag it down. We'll
paste it on in here. Drag it down. We'll open up up into the focus mode. And the
open up up into the focus mode. And the first thing, as always, I'm going to
first thing, as always, I'm going to change that title to make sure we stay
change that title to make sure we stay on task. And we'll change this to salary
on task. And we'll change this to salary verse hourly pay of data jobs. I don't
verse hourly pay of data jobs. I don't always do questions. I also sometimes do
always do questions. I also sometimes do things like verses. People love verses.
things like verses. People love verses. And so if you do that in this case, it
And so if you do that in this case, it gives them cues them in of what they
gives them cues them in of what they should be looking at in the
should be looking at in the visualization. Now let's actually format
visualization. Now let's actually format this into what we want. We want either a
this into what we want. We want either a line and stack column chart or line and
line and stack column chart or line and stack clustered column chart. Doesn't
stack clustered column chart. Doesn't really matter. We're only going to be
really matter. We're only going to be using one column with this. We have job
using one column with this. We have job title on the x-axis, the column yaxis.
title on the x-axis, the column yaxis. I'm going to update this to median
I'm going to update this to median yearly salary and add USD onto it. And
yearly salary and add USD onto it. And now we have the line yaxis. I'm going to
now we have the line yaxis. I'm going to drag salary hour average into this. And
drag salary hour average into this. And right now it's doing a sum. I don't want
right now it's doing a sum. I don't want it to do a sum. I want it to do a
it to do a sum. I want it to do a median. And if you notice with that,
median. And if you notice with that, whenever I click that, it then because
whenever I click that, it then because the values weren't the same or couldn't
the values weren't the same or couldn't match up with the original yaxis, it
match up with the original yaxis, it created a secondary yaxis. I'm going to
created a secondary yaxis. I'm going to change the title of this to median
change the title of this to median hourly salary USD. Now, one thing I
hourly salary USD. Now, one thing I could do to dress this up is I could add
could do to dress this up is I could add what's down here of data labels. We're
what's down here of data labels. We're going to go ahead and turn this on. This
going to go ahead and turn this on. This is data labels that are applied to all
is data labels that are applied to all series. I could adjust it to only do the
series. I could adjust it to only do the hourly. Anyway, so data labels hasn't
hourly. Anyway, so data labels hasn't been working properly. I'm going to go
been working properly. I'm going to go ahead. Let's actually try. We want to do
ahead. Let's actually try. We want to do it only the hourly salaries. I've
it only the hourly salaries. I've clicked series. I want to apply this to
clicked series. I want to apply this to hourly salaries. Turn on. Okay, it's on.
hourly salaries. Turn on. Okay, it's on. It's working. If I want to do yearly, I
It's working. If I want to do yearly, I can click yearly and then toggle this
can click yearly and then toggle this on. Or if I want to toggle it off. Let's
on. Or if I want to toggle it off. Let's say we want to do just the hourly. We
say we want to do just the hourly. We can display it this way. Personally, I
can display it this way. Personally, I feel like there's too much information
feel like there's too much information on this. I'm not going to apply data
on this. I'm not going to apply data labels to this type of visualization. If
labels to this type of visualization. If we go back to our actual first
we go back to our actual first visualization, this would be more one
visualization, this would be more one that I would apply data labels to. And
that I would apply data labels to. And with this, I could do things like add a
with this, I could do things like add a background to make it call out a little
background to make it call out a little bit better of what's going on with it.
bit better of what's going on with it. And then also going into value, making
And then also going into value, making it something like bold, so it's a little
it something like bold, so it's a little bit easier to actually read. And bam.
bit easier to actually read. And bam. Yeah, that's actually pretty good. Not
Yeah, that's actually pretty good. Not too bad. In this case, if I were to have
too bad. In this case, if I were to have the data labels, I'd most likely turn
the data labels, I'd most likely turn off something like the y-axis, like the
off something like the y-axis, like the values and the title because it already
values and the title because it already has it there. Additionally, under the
has it there. Additionally, under the grid lines, I just think that's too
grid lines, I just think that's too much. I could turn it off there. And now
much. I could turn it off there. And now I have a more simplistic view of what's
I have a more simplistic view of what's going on here with the data. So that is
going on here with the data. So that is line and also area charts or combo
line and also area charts or combo charts if you will. Out of all these,
charts if you will. Out of all these, the line chart is the most common right
the line chart is the most common right after column and bar. So, it pays to
after column and bar. So, it pays to know how to format this bad boy. All
know how to format this bad boy. All right, you now have some practice
right, you now have some practice problems to go through and get more
problems to go through and get more familiar with how to use these different
familiar with how to use these different types of charts. In the next lesson,
types of charts. In the next lesson, we're going to be jumping into other
we're going to be jumping into other common types of charts such as pie,
common types of charts such as pie, donut, tree map, and even scatter plots.
donut, tree map, and even scatter plots. With that, I'll see you there.
In this lesson, we're going to be covering other common types of charts.
covering other common types of charts. We still will be covering some more
We still will be covering some more after this, but I don't feel that
after this, but I don't feel that they're as common as these here and also
they're as common as these here and also those line and column and bar charts.
those line and column and bar charts. So, let's jump in and see what we're
So, let's jump in and see what we're going to be making for this. First up,
going to be making for this. First up, it's a pie chart. And in this, we're
it's a pie chart. And in this, we're analyzing what portion of job postings
analyzing what portion of job postings don't mention a degree. Remember, our
don't mention a degree. Remember, our data sets on job postings. Sometimes
data sets on job postings. Sometimes they mention a degree or they don't.
they mention a degree or they don't. This marks true when it doesn't mention
This marks true when it doesn't mention a degree. Anyway, we'll make a pie chart
a degree. Anyway, we'll make a pie chart out of this. And then similarly, we'll
out of this. And then similarly, we'll make a donut chart, which is basically a
make a donut chart, which is basically a pie chart with a giant hole in the
pie chart with a giant hole in the middle, but instead of doing postings
middle, but instead of doing postings that don't mention a degree, we're going
that don't mention a degree, we're going to do which job postings are marked as
to do which job postings are marked as work from home. Something kind of like
work from home. Something kind of like doing. Next, we'll get into making a
doing. Next, we'll get into making a tree map, which is this bad boy. And in
tree map, which is this bad boy. And in this, we're showing what are the types
this, we're showing what are the types of data jobs. Basically, it could be
of data jobs. Basically, it could be something like full-time, contractor,
something like full-time, contractor, internship, part-time, or even temp
internship, part-time, or even temp work. Tree maps are really good because
work. Tree maps are really good because whenever you have them with other
whenever you have them with other visualizations, people want to click on
visualizations, people want to click on them and you'll be able to filter your
them and you'll be able to filter your data down to what you want to actually
data down to what you want to actually see. Anyway, the last visualization
see. Anyway, the last visualization we're going to be doing is a scatter
we're going to be doing is a scatter plot, which is going to look at the hour
plot, which is going to look at the hour median salary verse the yearly median
median salary verse the yearly median salary for different job titles. And as
salary for different job titles. And as we're going to come to find out, there's
we're going to come to find out, there's definitely a trend between the two.
definitely a trend between the two. So here's the visualization we're going
So here's the visualization we're going to be building and it's looking at what
to be building and it's looking at what portions of postings don't mention
portions of postings don't mention degree. Remember we're using that field
degree. Remember we're using that field of job no degree mention. I think in the
of job no degree mention. I think in the intro I said it dimensions degree had
intro I said it dimensions degree had that backwards. It's what portion of job
that backwards. It's what portion of job postings don't mention degree. So in our
postings don't mention degree. So in our common charts canvas we're going to come
common charts canvas we're going to come in and insert a pie chart. And after
in and insert a pie chart. And after resizing I'm going to enter into focus
resizing I'm going to enter into focus mode. Remember we want to use that job
mode. Remember we want to use that job no degree mentioned column. So I'm going
no degree mentioned column. So I'm going to actually minimize this. Put job note
to actually minimize this. Put job note degree mention into the legend and it's
degree mention into the legend and it's appearing the legend is appearing but
appearing the legend is appearing but nothing's appearing. So we actually have
nothing's appearing. So we actually have to put some values in. Specifically we
to put some values in. Specifically we want the count of that column. First
want the count of that column. First things first I'm going to adjust the
things first I'm going to adjust the title to make sure we stay on task.
title to make sure we stay on task. Change it to what portion of postings
Change it to what portion of postings don't mention degree. So not too bad. I
don't mention degree. So not too bad. I do want to do some cleanup. Mainly I
do want to do some cleanup. Mainly I don't like this legend. I'd rather have
don't like this legend. I'd rather have data labels saying what is true and what
data labels saying what is true and what is false. so they don't have to figure
is false. so they don't have to figure out which one's true and false from
out which one's true and false from this. So under visual, I'll go down to
this. So under visual, I'll go down to detail labels. And for the label
detail labels. And for the label contents, we want to have the category.
contents, we want to have the category. And I don't really care about the count.
And I don't really care about the count. So I'm going to go to category percent
So I'm going to go to category percent of total. Scrolling down to the values,
of total. Scrolling down to the values, we'll make this a little bit bigger. Not
we'll make this a little bit bigger. Not too bad. I don't really like that it has
too bad. I don't really like that it has two decimal places. I just want zero. So
two decimal places. I just want zero. So not too bad. So this is pretty good for
not too bad. So this is pretty good for the detail labels. Because of that, I
the detail labels. Because of that, I don't want the legend. I'm going to go
don't want the legend. I'm going to go ahead and turn that off. Now, anytime
ahead and turn that off. Now, anytime I'm making a pie chart, I typically want
I'm making a pie chart, I typically want to use only two to three values in it.
to use only two to three values in it. That's why we're doing this true or
That's why we're doing this true or false here. And with it, right, the
false here. And with it, right, the question is what portion of postings
question is what portion of postings don't mention degrees. So, immediately I
don't mention degrees. So, immediately I want their eye to go to true. So, I do
want their eye to go to true. So, I do want true to be darker in this. However,
want true to be darker in this. However, I'm not really a fan of the colors. So,
I'm not really a fan of the colors. So, I'm going to go into slices. The true,
I'm going to go into slices. The true, we're going to maintain this dark blue.
we're going to maintain this dark blue. But for this false, I want a much
But for this false, I want a much lighter color. We'll leave it in the
lighter color. We'll leave it in the same palette even. And we'll make it
same palette even. And we'll make it this one. This, in my opinion, is much
this one. This, in my opinion, is much more readable and it draws it into where
more readable and it draws it into where they need to go. So, as we can see from
they need to go. So, as we can see from this, onethirds of job postings in
this, onethirds of job postings in general for all jobs don't mention the
general for all jobs don't mention the degree in the job posting.
Next one to make is a donut chart. This one will be pretty easy in however we're
one will be pretty easy in however we're changing it up. We're going to be
changing it up. We're going to be looking at what portion of job postings
looking at what portion of job postings are work from home. So I'm going to take
are work from home. So I'm going to take our original pie chart, control C it and
our original pie chart, control C it and control V it. Drag it up to the top
control V it. Drag it up to the top right hand corner and then I'm going to
right hand corner and then I'm going to change this into a doughnut chart. Now
change this into a doughnut chart. Now with this one and we're looking at work
with this one and we're looking at work from home and we have a column on that
from home and we have a column on that that's also a true and false value. So
that's also a true and false value. So two values. So perfect for this. So, I'm
two values. So perfect for this. So, I'm going to drag that into the legend
going to drag that into the legend itself and take out job no degree
itself and take out job no degree mention along with putting that jerk
mention along with putting that jerk work from home job work from home in the
work from home job work from home in the values and removing that job no degree
values and removing that job no degree mention. Put this bad boy into focus
mention. Put this bad boy into focus mode. As always, we're going to update
mode. As always, we're going to update that title first to what portion of
that title first to what portion of postings are work from home. I'm not a
postings are work from home. I'm not a fan of the coloring scheme once again.
fan of the coloring scheme once again. So, we'll change that true to that dark
So, we'll change that true to that dark color and we'll change the false to the
color and we'll change the false to the lighter one. All right. Not bad. I am
lighter one. All right. Not bad. I am noticing though the tool tips. Right.
noticing though the tool tips. Right. Um, it is it's very verbose in what it
Um, it is it's very verbose in what it has there. We do need to update that.
has there. We do need to update that. And I changed it to is work from home
And I changed it to is work from home and job count. So, is work from home
and job count. So, is work from home true. Looks like job count. It's like
true. Looks like job count. It's like 63,000 jobs or 13%. Don't forget also
63,000 jobs or 13%. Don't forget also when we probably need to update that pie
when we probably need to update that pie chart as well. Now, when you scroll over
chart as well. Now, when you scroll over it, we can see, hey, is no degree
it, we can see, hey, is no degree mentioned? True. And the count, which
mentioned? True. And the count, which count didn't update. Okay, that's
count didn't update. Okay, that's looking better.
looking better. Next up is tree map. And this is really
Next up is tree map. And this is really good visualization to show a breakdown
good visualization to show a breakdown of what's available. But mainly I like
of what's available. But mainly I like it because if we actually go back to the
it because if we actually go back to the report itself with everything else on it
report itself with everything else on it makes it to where you want to actually
makes it to where you want to actually interact with it. So in the case of the
interact with it. So in the case of the tree map, if I wanted to look at just
tree map, if I wanted to look at just full-time roles, I can click on that and
full-time roles, I can click on that and then all the other data filters for
then all the other data filters for that. So it's a great way to draw users
that. So it's a great way to draw users in and interact with your report. So
in and interact with your report. So inside of here, we're going to click
inside of here, we're going to click here and we're going to add a tree map.
here and we're going to add a tree map. I'm going to drag it to the bottom right
I'm going to drag it to the bottom right hand corner. Go into focus mode. For
hand corner. Go into focus mode. For this, we're using a new column we
this, we're using a new column we haven't used yet. It's this job schedule
haven't used yet. It's this job schedule type. And job schedule type has
type. And job schedule type has different values in it. Actually has
different values in it. Actually has this actually needs a lot of cleanup,
this actually needs a lot of cleanup, but it has things like contractor,
but it has things like contractor, full-time, part-time, PDM, temp work.
full-time, part-time, PDM, temp work. We'll actually get into cleaning this up
We'll actually get into cleaning this up in the next chapter in chapter three uh
in the next chapter in chapter three uh chapter 3 on Power Query. So stand by
chapter 3 on Power Query. So stand by for that. Anyway, we're going to drag
for that. Anyway, we're going to drag this job schedule type into the
this job schedule type into the categories and then also drag it into
categories and then also drag it into the values. First thing I want to do
the values. First thing I want to do like usual is update the title to what
like usual is update the title to what are the type of data jobs. Now there's a
are the type of data jobs. Now there's a few too many values here. You can see
few too many values here. You can see it's even breaking down further in the
it's even breaking down further in the bottom right hand corner. I want to
bottom right hand corner. I want to filter this down to only specific values
filter this down to only specific values for the job schedule type. Specifically,
for the job schedule type. Specifically, if I move over this filter, whenever it
if I move over this filter, whenever it has multiple different ones like
has multiple different ones like contractor and full-time, contractor to
contractor and full-time, contractor to internship, there's only like two, 45,
internship, there's only like two, 45, 40. I don't really want those. I want
40. I don't really want those. I want just the single value. So, in this case,
just the single value. So, in this case, contractor, full-time, internship,
contractor, full-time, internship, part-time, PDM doesn't have a lot, so
part-time, PDM doesn't have a lot, so we're not going to do that. We'll do
we're not going to do that. We'll do temp work and we'll call it good. Close
temp work and we'll call it good. Close out of this filters pane. So, at least a
out of this filters pane. So, at least a little bit more readable in what are the
little bit more readable in what are the different selections and the top values
different selections and the top values uh that we can get. Now, I'm not a big
uh that we can get. Now, I'm not a big fan of all these different colors,
fan of all these different colors, especially if you go back to your
especially if you go back to your report. Like, it just doesn't match the
report. Like, it just doesn't match the palette that we're doing here. And also,
palette that we're doing here. And also, in general, I don't like a lot of
in general, I don't like a lot of different colors. It gets visually
different colors. It gets visually distracting. Your users won't know where
distracting. Your users won't know where to put their eyes. In our case, we do
to put their eyes. In our case, we do want their eyes to go to probably the
want their eyes to go to probably the most the biggest value, if you will. So,
most the biggest value, if you will. So, once again, we want to get this darker.
once again, we want to get this darker. And then the other values, these smaller
And then the other values, these smaller ones, we want a little bit lighter. So
ones, we want a little bit lighter. So what we can do is under format visual
what we can do is under format visual under colors, we could change each one
under colors, we could change each one of these colors individually for what it
of these colors individually for what it is. Like if I want to change this to
is. Like if I want to change this to contractor to pink. I'm not really a fan
contractor to pink. I'm not really a fan of this. Instead, we go into advanced
of this. Instead, we go into advanced controls and use this conditional
controls and use this conditional formatting. Under the format style,
formatting. Under the format style, we're going to change this into a
we're going to change this into a gradient. And let's change this into
gradient. And let's change this into those colors. So for the minimum value,
those colors. So for the minimum value, let's use what we were using previously,
let's use what we were using previously, this light color theme. And then for the
this light color theme. And then for the maximum value, we're going to use the
maximum value, we're going to use the darker one of this. This looks okay.
darker one of this. This looks okay. Click okay. And bam. Now we have
Click okay. And bam. Now we have something that's a lot more manageable
something that's a lot more manageable in the eyesight. And when compared to
in the eyesight. And when compared to all our other visuals, it fits in in the
all our other visuals, it fits in in the visuals on where we want them to draw
visuals on where we want them to draw their attention. Last thing we need to
their attention. Last thing we need to do is just update the tool tips for
do is just update the tool tips for this. We'll call this one schedule type
this. We'll call this one schedule type for the category and then for the
for the category and then for the values, job count. All right, not too
values, job count. All right, not too bad. getting this back into focus mode.
bad. getting this back into focus mode. The other thing that we want to do is we
The other thing that we want to do is we want to put because right now we can see
want to put because right now we can see it, but what is the relative percentage
it, but what is the relative percentage of each of these relative to each other?
of each of these relative to each other? So, what I'm going to do is come in here
So, what I'm going to do is come in here under format visual under the data
under format visual under the data labels. I'm going to go ahead and turn
labels. I'm going to go ahead and turn them on. And if you notice, they're
them on. And if you notice, they're actually a count. I don't really want
actually a count. I don't really want count, but we'll deal with that for the
count, but we'll deal with that for the time being. We will change, however, the
time being. We will change, however, the value decimal places to zero. And I will
value decimal places to zero. And I will make them slightly bigger. Now, like I
make them slightly bigger. Now, like I said, I don't want to count for here. I
said, I don't want to count for here. I can't change this percentage inside of
can't change this percentage inside of here. But what I can do is going into
here. But what I can do is going into values, clicking on this down arrow.
values, clicking on this down arrow. Right now, we have count. But then we
Right now, we have count. But then we have this show value as we could do no
have this show value as we could do no calculation or percent of grand total,
calculation or percent of grand total, which is actually exactly what we want.
which is actually exactly what we want. We see that full-time jobs are 90% of
We see that full-time jobs are 90% of the job postings, contractors are 7%,
the job postings, contractors are 7%, internships are less than 1%, and
internships are less than 1%, and following.
The last visualization to make is a scatter plot. Scatter plots are great at
scatter plot. Scatter plots are great at showing the relationship between two
showing the relationship between two different values. In this case, we can
different values. In this case, we can show the relationship between hourly and
show the relationship between hourly and yearly median salary for these different
yearly median salary for these different job titles. So, let's put this bad boy
job titles. So, let's put this bad boy together. In our canvas, we're going to
together. In our canvas, we're going to throw in this scatter chart. I'm going
throw in this scatter chart. I'm going to go into focus mode. For this one,
to go into focus mode. For this one, we're going to just start off instead of
we're going to just start off instead of doing the values, we're going to start
doing the values, we're going to start with that x-axis, putting the yearly
with that x-axis, putting the yearly salary data there and then the hourly in
salary data there and then the hourly in the y ais. For both of these, we want to
the y ais. For both of these, we want to aggregate by the median. Then we want to
aggregate by the median. Then we want to break it up right by the job title. So,
break it up right by the job title. So, we need to put in the legend that job
we need to put in the legend that job title short. All right, not too bad.
title short. All right, not too bad. Before we get too far, I do want to
Before we get too far, I do want to update the title on this to hourly verse
update the title on this to hourly verse yearly salary of data jobs. People love
yearly salary of data jobs. People love some verses. I'm also going to clean up
some verses. I'm also going to clean up what's in the field well to make these
what's in the field well to make these values more readable. So there's a lot
values more readable. So there's a lot more readable. We can see what's up here
more readable. We can see what's up here in the top right hand corner. Machine
in the top right hand corner. Machine learning engineers have 155,000 for the
learning engineers have 155,000 for the hour for the yearly salary, $60 for the
hour for the yearly salary, $60 for the hourly salary. Might need to consider
hourly salary. Might need to consider changing my job. Anyway, once again, if
changing my job. Anyway, once again, if I go back to the actual report pane,
I go back to the actual report pane, look at this. I mean, the the coloring
look at this. I mean, the the coloring on this just doesn't match the other
on this just doesn't match the other pallets. And two, it's just highly
pallets. And two, it's just highly distracting. If I go back into focus
distracting. If I go back into focus mode, where the heck do you need to look
mode, where the heck do you need to look on this? Well, with a scatter plot in
on this? Well, with a scatter plot in general, I don't want to necessarily
general, I don't want to necessarily draw your attention any specific
draw your attention any specific location in this kind of manner. So, I
location in this kind of manner. So, I want to probably just remove the colors.
want to probably just remove the colors. However, this one's a little bit more
However, this one's a little bit more tricky. In this case, we're going to go
tricky. In this case, we're going to go to format your visual and we go to
to format your visual and we go to markers and expanding it out and
markers and expanding it out and scrolling on down to colors. If I try
scrolling on down to colors. If I try to, it doesn't let me change the color.
to, it doesn't let me change the color. I can, however, change the transparency.
I can, however, change the transparency. We're going to take that transparency to
We're going to take that transparency to 100%. Basically, not make it 100%
100%. Basically, not make it 100% transparent. You can't visual visualize
transparent. You can't visual visualize it. And I'm going to go into border.
it. And I'm going to go into border. With this, I'm going to uncheck the
With this, I'm going to uncheck the match fill color. And now, you see all
match fill color. And now, you see all of them are this dark gray color. What I
of them are this dark gray color. What I can do is I can come in and make it that
can do is I can come in and make it that dark blue color that I like. And I can
dark blue color that I like. And I can make the width of this bigger. That's a
make the width of this bigger. That's a little bit too big. I could also adjust
little bit too big. I could also adjust the transparency on this, but then my
the transparency on this, but then my visuals aren't available. Okay. So, not
visuals aren't available. Okay. So, not bad. But I'd argue it still needs well
bad. But I'd argue it still needs well one this is highly confusing because I
one this is highly confusing because I have this job title legend up here with
have this job title legend up here with colors and none of it correlates. So
colors and none of it correlates. So under format visual under the same thing
under format visual under the same thing I'm going to turn off the legend first
I'm going to turn off the legend first and then under category labels I'm going
and then under category labels I'm going to turn this on. This is allows us to
to turn this on. This is allows us to now format those different uh category
now format those different uh category labels. I made it slightly bigger and we
labels. I made it slightly bigger and we can actually see where everything falls
can actually see where everything falls and we can see something like data
and we can see something like data analyst is down at the bottom left hand
analyst is down at the bottom left hand corner. Oh gosh. All right. So, not too
corner. Oh gosh. All right. So, not too bad. Anytime I have any of these scatter
bad. Anytime I have any of these scatter plots, I would want to I want to see is
plots, I would want to I want to see is there some sort of relationship. I could
there some sort of relationship. I could in this case put in a trend line, make
in this case put in a trend line, make it a lighter color and a little bit
it a lighter color and a little bit transparent so it doesn't like take up
transparent so it doesn't like take up the entire thing. And then bam, we can
the entire thing. And then bam, we can actually see, okay, in queue our end
actually see, okay, in queue our end users in, there is actually a trend. If
users in, there is actually a trend. If there's a higher yearly salary, there's
there's a higher yearly salary, there's probably going to be a higher median
probably going to be a higher median hourly salary. Those that have senior
hourly salary. Those that have senior roles, like senior data engineers,
roles, like senior data engineers, senior data scientists are going to pay
senior data scientists are going to pay more than their counterparts. Well, at
more than their counterparts. Well, at least in some cases, looks like this
least in some cases, looks like this data engineer in hourly gets paid more
data engineer in hourly gets paid more than senior data engineer in their
than senior data engineer in their hourly. There's no
hourly. There's no there's no more visuals to build, but I
there's no more visuals to build, but I want to talk about a feature within
want to talk about a feature within PowerBI dealing with editing
PowerBI dealing with editing interactions. If you remember from
interactions. If you remember from earlier, I talked about with this tree
earlier, I talked about with this tree map. It's great because I can click it
map. It's great because I can click it and then it will filter other data. But
and then it will filter other data. But let's do something like I'm going to
let's do something like I'm going to click contractor, which has less. What
click contractor, which has less. What the heck am I supposed to make out of
the heck am I supposed to make out of this doughut chart? And what the heck am
this doughut chart? And what the heck am I supposed to make out of this pie
I supposed to make out of this pie chart? Like I'm not even like you can
chart? Like I'm not even like you can see they're not even the same size. I'm
see they're not even the same size. I'm supposed to do the math on my head and
supposed to do the math on my head and try to figure out how they are
try to figure out how they are different. Basically, I'm not liking how
different. Basically, I'm not liking how they're crossfiltered. Well, that's
they're crossfiltered. Well, that's where if we go into the format tab, they
where if we go into the format tab, they have this edit interactions. I'm going
have this edit interactions. I'm going to go ahead and click it and it stays
to go ahead and click it and it stays clicked. As you notice this, these icons
clicked. As you notice this, these icons popped up and then when I turn it off,
popped up and then when I turn it off, those icons pop away. So, this enables
those icons pop away. So, this enables you to edit interactions. But there's
you to edit interactions. But there's only one icon here that there's a
only one icon here that there's a there's actually a little bit of a bug
there's actually a little bit of a bug with PowerBI. You can't see some of
with PowerBI. You can't see some of these visualizations and their
these visualizations and their appropriate things for edit interaction.
appropriate things for edit interaction. So I'm going to make these other charts
So I'm going to make these other charts a little bit smaller. Now we can see
a little bit smaller. Now we can see when I'm clicked on the tree map, all
when I'm clicked on the tree map, all these other three around these have
these other three around these have these options to edit the interactions.
these options to edit the interactions. Anyway, the easiest one to understand is
Anyway, the easiest one to understand is for the tree map, right? I can turn off
for the tree map, right? I can turn off to make it none for all of these, right?
to make it none for all of these, right? So they're not getting filtered. So as a
So they're not getting filtered. So as a test, whenever I I just turned off edit
test, whenever I I just turned off edit interactions as a test, I can click
interactions as a test, I can click different things in here and none of the
different things in here and none of the other ones are getting or having
other ones are getting or having affected. However, whenever I go to the
affected. However, whenever I go to the pie chart, it is interacting with
pie chart, it is interacting with others, right? I I did it specifically
others, right? I I did it specifically for this tree map. Now, I typically
for this tree map. Now, I typically don't use this none. Let my turn back on
don't use this none. Let my turn back on edit interactions. I typically don't use
edit interactions. I typically don't use this none to remove the filtering.
this none to remove the filtering. Remember, by default, it was on this
Remember, by default, it was on this highlight for at least for the pie
highlight for at least for the pie charts. For this scatter plot, they only
charts. For this scatter plot, they only have one option, and that's only filter.
have one option, and that's only filter. We're going to leave scatter plot as
We're going to leave scatter plot as filter. Anyway, with the tree map
filter. Anyway, with the tree map selected, let's change these other ones
selected, let's change these other ones now from being highlight to filter. I'm
now from being highlight to filter. I'm going to change it for that. And also
going to change it for that. And also the pie chart. Now, whenever I click the
the pie chart. Now, whenever I click the tree map and filter down, notice what it
tree map and filter down, notice what it does. it doesn't actually do that
does. it doesn't actually do that shrinking down. It actually adjusts the
shrinking down. It actually adjusts the actual pie chart itself and uh donut
actual pie chart itself and uh donut chart. So it makes a lot more readable.
chart. So it makes a lot more readable. However, this is just for the tree map.
However, this is just for the tree map. If I go over to the scatter plot, I'm
If I go over to the scatter plot, I'm going to look at something like data
going to look at something like data engineers and I clicked on this. It's
engineers and I clicked on this. It's still going to do this option. Notice
still going to do this option. Notice now I'm selected on the scatter plot.
now I'm selected on the scatter plot. This for the pie chart is on highlight.
This for the pie chart is on highlight. I'm going to change this to filter. And
I'm going to change this to filter. And for the doughut chart, I'm going to
for the doughut chart, I'm going to change it also to filter. Okay, now just
change it also to filter. Okay, now just testing it. Yep, it's getting adjusted.
testing it. Yep, it's getting adjusted. Two more I want to update for this. So,
Two more I want to update for this. So, same thing. I'm going to select the pie
same thing. I'm going to select the pie chart. Click in here. Don't like how
chart. Click in here. Don't like how it's doing it. I'm going to change this
it's doing it. I'm going to change this one. And then it click into the doughut
one. And then it click into the doughut chart. Going to click this one. Oh,
chart. Going to click this one. Oh, don't like how it's done. Going to
don't like how it's done. Going to change this one to filter. And now
change this one to filter. And now everything is back or at least in
everything is back or at least in configured in a way that I actually like
configured in a way that I actually like it. And so I can make these charts back
it. And so I can make these charts back to the same size they were. Basically
to the same size they were. Basically hid those icons that were being hidden
hid those icons that were being hidden andclick edit interactions. Now just
andclick edit interactions. Now just testing it out. Can click contractor.
testing it out. Can click contractor. Yep, everything filters down. I can
Yep, everything filters down. I can click the true portion of work from
click the true portion of work from home. Yep, everything filters down like
home. Yep, everything filters down like I want. So edit interactions is sort of
I want. So edit interactions is sort of an advanced concept to understand get
an advanced concept to understand get through. So that's why we have some
through. So that's why we have some practice problems to now for you to go
practice problems to now for you to go through not only build those pie and
through not only build those pie and those doughnut charts, but also get some
those doughnut charts, but also get some familiarity with how to use edit
familiarity with how to use edit interactions. With that, I'll see you in
interactions. With that, I'll see you in the next one.
Welcome to this lesson on maps. And although I use these less frequently
although I use these less frequently like thing than things like bar charts,
like thing than things like bar charts, column charts or line charts, these do
column charts or line charts, these do these map visuals do have their place
these map visuals do have their place from time to time. So let's jump in into
from time to time. So let's jump in into understanding what we're actually going
understanding what we're actually going to be doing for this lesson in building
to be doing for this lesson in building three different maps. Now PowerBI by
three different maps. Now PowerBI by default has three different map types.
default has three different map types. The first one is called just map. Really
The first one is called just map. Really special, I know. The second one is
special, I know. The second one is called field map because it looks like a
called field map because it looks like a field map. And then the third one right
field map. And then the third one right here is ArcGIS for PowerBI map.
here is ArcGIS for PowerBI map. Basically, they want you to buy the
Basically, they want you to buy the extra ArcGIS. We'll get into all that in
extra ArcGIS. We'll get into all that in a little bit. Anyway, for the basic
a little bit. Anyway, for the basic first map overview, we're going to be
first map overview, we're going to be looking at which countries don't mention
looking at which countries don't mention degrees in their job postings. This
degrees in their job postings. This displays a dot over our specified
displays a dot over our specified location, in our case, country. And the
location, in our case, country. And the size of it is relative, in our case, to
size of it is relative, in our case, to the job count. We can also break it down
the job count. We can also break it down further into this pie chart inside of
further into this pie chart inside of here for true or false values. In our
here for true or false values. In our case, true that it doesn't mention a
case, true that it doesn't mention a degree in the job posting. Next up is
degree in the job posting. Next up is our filled map. And I'll be honest, out
our filled map. And I'll be honest, out of all the maps here, find this the most
of all the maps here, find this the most useless, but I do want to cover it
useless, but I do want to cover it anyway. It fills in a certain color. In
anyway. It fills in a certain color. In this case, we're just filtering the
this case, we're just filtering the color based on what country is which
color based on what country is which country, which in my mind, I'm like, I
country, which in my mind, I'm like, I don't really care about that. That's why
don't really care about that. That's why I'm not really that big of a fan of this
I'm not really that big of a fan of this type of map, although I do want to go
type of map, although I do want to go through it so you're aware of it. Now,
through it so you're aware of it. Now, the last one I actually like the most of
the last one I actually like the most of RGis for PowerBI. And this one, we're
RGis for PowerBI. And this one, we're looking at what are the highest paying
looking at what are the highest paying jobs globally. Here you can see, well,
jobs globally. Here you can see, well, this country right here, this big one
this country right here, this big one has the highest paying. Kind of fishy.
has the highest paying. Kind of fishy. Anyway, this one's going to come with a
Anyway, this one's going to come with a little bit of a catch. not not the
little bit of a catch. not not the country, the map itself. And so my main
country, the map itself. And so my main recommended one is this first one.
recommended one is this first one. So let's get into building these map
So let's get into building these map visuals. We're going to start by
visuals. We're going to start by creating a new page. And I'm going to
creating a new page. And I'm going to call this map charts. Now, if you didn't
call this map charts. Now, if you didn't actually work through the first chapter
actually work through the first chapter in this, you're going to come to find
in this, you're going to come to find out that the map charts aren't going to
out that the map charts aren't going to work. We have to actually enable them.
work. We have to actually enable them. And this is done by going into file and
And this is done by going into file and then options and settings and then
then options and settings and then options. I'm going to navigate down here
options. I'm going to navigate down here under global to security. And for this,
under global to security. And for this, we want to make sure that custom v uh
we want to make sure that custom v uh visuals are enabled. ArcJS for PowerBI,
visuals are enabled. ArcJS for PowerBI, which is one of the maps, and then the
which is one of the maps, and then the map and field map visuals are also
map and field map visuals are also enabled. These are the main two that you
enabled. These are the main two that you need for this lesson. Now, if you set up
need for this lesson. Now, if you set up a PowerBI Pro license and you've
a PowerBI Pro license and you've connected it to your PowerBI app, you
connected it to your PowerBI app, you may need to take these additional steps
may need to take these additional steps that I did in order to enable it in the
that I did in order to enable it in the PowerBI service so you don't get black
PowerBI service so you don't get black blocked from doing it in the app. If you
blocked from doing it in the app. If you didn't set up a free or pro account with
didn't set up a free or pro account with PowerBI, this portion is not applicable
PowerBI, this portion is not applicable to you. Anyway, I'm going to go to the
to you. Anyway, I'm going to go to the settings icon up here and I'm going to
settings icon up here and I'm going to navigate to the admin portal. In the
navigate to the admin portal. In the search bar over here, I'm going to type
search bar over here, I'm going to type in map. And for this I want to ensure
in map. And for this I want to ensure that use RGIs maps for PowerBI is
that use RGIs maps for PowerBI is enabled and also that the map and field
enabled and also that the map and field map visuals are enabled. Whenever you
map visuals are enabled. Whenever you enable them you need to then go ahead
enable them you need to then go ahead and apply. And like usual this can take
and apply. And like usual this can take up to 15 minutes to work.
up to 15 minutes to work. So while you're waiting for that to
So while you're waiting for that to load, let's jump into building our first
load, let's jump into building our first map visual. And like again this is going
map visual. And like again this is going to be looking at which countries don't
to be looking at which countries don't mention degrees in their job postings.
mention degrees in their job postings. in our blank canvas. I'm going to select
in our blank canvas. I'm going to select map. I'll move it into that top
map. I'll move it into that top quadrant. And then we go into focus
quadrant. And then we go into focus mode. All right. For this one, we're
mode. All right. For this one, we're going to be using we want to aggregate
going to be using we want to aggregate it by the job country location. So, I'm
it by the job country location. So, I'm going to go ahead and put that in here.
going to go ahead and put that in here. Now, notice there's a dot now for each
Now, notice there's a dot now for each of the countries. And just as a
of the countries. And just as a reminder, just so you can check it out,
reminder, just so you can check it out, I could I'm going to X out of this this
I could I'm going to X out of this this job country. And I'm going to drag job
job country. And I'm going to drag job location onto here. If you notice by
location onto here. If you notice by this, there's a lot more dots on here.
this, there's a lot more dots on here. If I scroll over it, these get very more
If I scroll over it, these get very more in deep uh detail. Like this was from
in deep uh detail. Like this was from Crawford'sville, Indiana. If you're
Crawford'sville, Indiana. If you're watching this from there, Indiana, give
watching this from there, Indiana, give a comment in the video below. Anyway,
a comment in the video below. Anyway, we'll use job location at a different
we'll use job location at a different time, but right now, this is just too
time, but right now, this is just too much data on this map visual. I don't
much data on this map visual. I don't like it. I'm going to go ahead and X out
like it. I'm going to go ahead and X out of it. Instead, we're going to drop job
of it. Instead, we're going to drop job country down into location. Now, this
country down into location. Now, this also has the option for using latitude
also has the option for using latitude and longitude and this will be
and longitude and this will be applicable to all the map visuals that
applicable to all the map visuals that we have. This results in even more
we have. This results in even more precise data because sometimes your
precise data because sometimes your location data isn't going to populate in
location data isn't going to populate in this map chart because it's not able to
this map chart because it's not able to figure it out on where it needs to go.
figure it out on where it needs to go. So, if you have latitude and longitude
So, if you have latitude and longitude data, which we don't have in this case,
data, which we don't have in this case, I recommend you use that instead because
I recommend you use that instead because it's more precise. Now, let's make these
it's more precise. Now, let's make these bubbles a different size. We're going to
bubbles a different size. We're going to use this bubble size. I'm going to drag
use this bubble size. I'm going to drag job title short into here and it's now
job title short into here and it's now going to do a count of job title short.
going to do a count of job title short. I'm going to rename this down to job
I'm going to rename this down to job count and then also this location to
count and then also this location to country. So that way whenever I scroll
country. So that way whenever I scroll over something like the United States, I
over something like the United States, I can see that hey the country is United
can see that hey the country is United States and the job count is 140,000
States and the job count is 140,000 jobs. Now remember, we want to see the
jobs. Now remember, we want to see the breakdown of what countries don't
breakdown of what countries don't mention a degree requirement in the job
mention a degree requirement in the job posting. So, I'm going to take job no
posting. So, I'm going to take job no degree mentioned and put it into the
degree mentioned and put it into the legend. I'm going to change this to no
legend. I'm going to change this to no degree mentioned. And now, scrolling
degree mentioned. And now, scrolling back over the United States, we can see
back over the United States, we can see that it's false for 109,000 values and
that it's false for 109,000 values and then it is true for 30,000 values. And
then it is true for 30,000 values. And so, I may I didn't update the title to
so, I may I didn't update the title to keep us on track and update it to which
keep us on track and update it to which countries don't mention degrees in job
countries don't mention degrees in job postings. Going back to that build
postings. Going back to that build visual, there's one other field that's
visual, there's one other field that's very common that's in basically every
very common that's in basically every single visualization and that's this
single visualization and that's this tool tips. We can add extra fields to
tool tips. We can add extra fields to this tool tips to appear. If I wanted
this tool tips to appear. If I wanted to, I could take that salary year
to, I could take that salary year average, drag it into here, make it into
average, drag it into here, make it into something like median, and then change
something like median, and then change this to median yearly salary. And now
this to median yearly salary. And now whenever I scroll over this, I can see
whenever I scroll over this, I can see that when there's no mention of a
that when there's no mention of a degree, the salary is $104,000
degree, the salary is $104,000 on median. But when there is a mention
on median. But when there is a mention of degree, it's 113,000. So it's a
of degree, it's 113,000. So it's a little bit higher whenever we do mention
little bit higher whenever we do mention a degree in there. Pretty interesting
a degree in there. Pretty interesting insight.
Next, let's get into the field map. Like I mentioned in the beginning, I'm not
I mentioned in the beginning, I'm not really a fan of this, so we're going to
really a fan of this, so we're going to kind of rush through it just so you're
kind of rush through it just so you're familiar with it and understand it. But
familiar with it and understand it. But as far as the capabilities, as I can see
as far as the capabilities, as I can see from this, or as you can see from this,
from this, or as you can see from this, I don't get a lot of insights out of it.
I don't get a lot of insights out of it. Back in our canvas, I'm going to go
Back in our canvas, I'm going to go ahead and insert a filled map. I'm going
ahead and insert a filled map. I'm going to start from scratch and not copy and
to start from scratch and not copy and paste just to make sure that you get it
paste just to make sure that you get it down of what we're actually doing here.
down of what we're actually doing here. We're going to use location field. And
We're going to use location field. And for specifically for that, we're going
for specifically for that, we're going to use job country. I'm going to go
to use job country. I'm going to go ahead and call this country. Next, right
ahead and call this country. Next, right underneath it is the legend. And as we
underneath it is the legend. And as we had in that final one, I can go ahead
had in that final one, I can go ahead and put job country into here and
and put job country into here and putting this into focus mode. This is
putting this into focus mode. This is giving me all sorts of colors. Anyway,
giving me all sorts of colors. Anyway, if I scroll over it, I can see things
if I scroll over it, I can see things like the tool tips to providing that it
like the tool tips to providing that it is what the country is. The other field
is what the country is. The other field in here that I wanted to do if tool tips
in here that I wanted to do if tool tips again, I could drag in that salary or
again, I could drag in that salary or average into here. Make that median and
average into here. Make that median and call that median yearly salary USD. Now,
call that median yearly salary USD. Now, when I scroll over to United States, I
when I scroll over to United States, I get that as well. Anyway, what I would
get that as well. Anyway, what I would hope would be more intuitive out of
hope would be more intuitive out of this, like something like the legend.
this, like something like the legend. Instead, let's say I wanted to color it
Instead, let's say I wanted to color it in like a scheme or a gradient using
in like a scheme or a gradient using something like the salary year average
something like the salary year average column. Now, it's going to go ahead and
column. Now, it's going to go ahead and color it, but it basically gives
color it, but it basically gives distinct colors for all the different
distinct colors for all the different values. Doesn't also even do aggregation
values. Doesn't also even do aggregation in the legend. Basically, it's a hot
in the legend. Basically, it's a hot mess. Not a fan of this bad boy. So, I'm
mess. Not a fan of this bad boy. So, I'm going to go ahead and put country back
going to go ahead and put country back in here. update the title to where our
in here. update the title to where our job postings globally. And we're going
job postings globally. And we're going to call it a day with this one.
to call it a day with this one. Now, where field maps fail, this is
Now, where field maps fail, this is where I like RGis. They come in handy
where I like RGis. They come in handy and they actually satisfies what I need.
and they actually satisfies what I need. In this case, we're going to go through
In this case, we're going to go through and actually make based on median salary
and actually make based on median salary what is the different color coding or
what is the different color coding or the color scheme necessary to actually
the color scheme necessary to actually get it to visually indicate what is the
get it to visually indicate what is the highest salary. So, back in our canvas,
highest salary. So, back in our canvas, I'm going to go ahead down here under
I'm going to go ahead down here under ArcJS for PowerBI. I'm going to insert
ArcJS for PowerBI. I'm going to insert it in. We're going to go into focus mode
it in. We're going to go into focus mode so we can actually read this. Now, this
so we can actually read this. Now, this is the main issue we're going to have
is the main issue we're going to have with ARGIS.
with ARGIS. We don't need to create a sign in. We're
We don't need to create a sign in. We're going to be able to go in and actually
going to be able to go in and actually continue as guest. But, as you notice,
continue as guest. But, as you notice, there is a sign in here. So, if we're
there is a sign in here. So, if we're going to go forward with sharing a
going to go forward with sharing a dashboard, specifically in the PowerBI
dashboard, specifically in the PowerBI service with an ARGIS visual, we're not
service with an ARGIS visual, we're not going to be able to do it unless your
going to be able to do it unless your company or you pay the thousands of
company or you pay the thousands of dollars to have an Argis subscription.
dollars to have an Argis subscription. Long story short, if you're just like a
Long story short, if you're just like a student or somebody like me, a solo
student or somebody like me, a solo entrepreneur, you can, yeah, use this to
entrepreneur, you can, yeah, use this to make graphs and visuals for you only,
make graphs and visuals for you only, but as soon as you want to start
but as soon as you want to start distributing to somebody else, you're
distributing to somebody else, you're going to have to pay a heck of a price.
going to have to pay a heck of a price. This is a report that I built that had
This is a report that I built that had an ArcJS for PowerBI in it that I
an ArcJS for PowerBI in it that I uploaded to the PowerBI service.
uploaded to the PowerBI service. Whenever I actually went to it and tried
Whenever I actually went to it and tried to use it with ARG uh ARGIS, it says
to use it with ARG uh ARGIS, it says this map does not meet the requirements
this map does not meet the requirements for publish reports. So, it's proof that
for publish reports. So, it's proof that you can't use it unless you're paying
you can't use it unless you're paying for it. Anyway, very similar. We can use
for it. Anyway, very similar. We can use latitude or longitude or the location.
latitude or longitude or the location. So, I'm going to drag job country into
So, I'm going to drag job country into that location column. And the visual
that location column. And the visual does take a second or two to load, but
does take a second or two to load, but loads nonetheless. and we'll change
loads nonetheless. and we'll change location to country. Then scrolling on
location to country. Then scrolling on down below latitude, longitude, we have
down below latitude, longitude, we have size and also color, time, and then also
size and also color, time, and then also tool tips and join layer. Oh, and find
tool tips and join layer. Oh, and find similar. We're going to just focus
similar. We're going to just focus mainly on size and color. Now, I'm going
mainly on size and color. Now, I'm going to start with the size and put salary
to start with the size and put salary year average into here. And in this
year average into here. And in this case, I'm going to change it to median.
case, I'm going to change it to median. Notice it is doing because I did size,
Notice it is doing because I did size, it's going to do size of the bubble
it's going to do size of the bubble sizes. And this thing, I'll be honest, I
sizes. And this thing, I'll be honest, I can't really read it. We can adjust it
can't really read it. We can adjust it later. But that's why we're actually
later. But that's why we're actually going to shift this one down into color
going to shift this one down into color as this is much more intuitive. Although
as this is much more intuitive. Although I don't like the color scheme of this.
I don't like the color scheme of this. This is much more intuitive of where are
This is much more intuitive of where are the higher salaries compared to
the higher salaries compared to everybody else. I'll change this to
everybody else. I'll change this to median yearly salary USD. Now, whenever
median yearly salary USD. Now, whenever I scroll over it, it's not providing
I scroll over it, it's not providing anything. Probably got to put this into
anything. Probably got to put this into tool tips. And then I'm going to change
tool tips. And then I'm going to change this to median yearly salary USD. Now
this to median yearly salary USD. Now scrolling over this, we don't get a
scrolling over this, we don't get a country anymore, but at least we're
country anymore, but at least we're getting the median value, which isn't
getting the median value, which isn't correct. What's going on here? I still
correct. What's going on here? I still have it on sum. I'm an idiot. I should
have it on sum. I'm an idiot. I should have it on median. Okay, median's out in
have it on median. Okay, median's out in the US. Looking a lot like more like the
the US. Looking a lot like more like the value that we need to have. Job country
value that we need to have. Job country is not appearing on here. So apparently
is not appearing on here. So apparently I got to drag this also into the tool
I got to drag this also into the tool tip. And now I'm getting country and
tip. And now I'm getting country and also median year. Okay, so that's
also median year. Okay, so that's basically all the formatting we're going
basically all the formatting we're going to do outside of here. The other thing
to do outside of here. The other thing we can do now to start formatting,
we can do now to start formatting, especially the color and how it's all
especially the color and how it's all set up is over here on this lefth hand
set up is over here on this lefth hand menu. This expand and collapses. The
menu. This expand and collapses. The next one gets into the layers. We can
next one gets into the layers. We can see a breakdown of how they're actually
see a breakdown of how they're actually breaking up the colors. And then we can
breaking up the colors. And then we can also go into symbology to change if we
also go into symbology to change if we want how we're doing the coloring by job
want how we're doing the coloring by job country. We don't want to mess with
country. We don't want to mess with that. We want actually go into the style
that. We want actually go into the style options. We're not going to change the
options. We're not going to change the shape cuz we're not doing shape, right?
shape cuz we're not doing shape, right? We're doing color. We're going to change
We're doing color. We're going to change this. And personally, I like the blues
this. And personally, I like the blues and I like this blue three to where
and I like this blue three to where higher values are darker in color.
higher values are darker in color. Closing this out just to inspect from
Closing this out just to inspect from it. Okay, this is getting what I want.
it. Okay, this is getting what I want. Other things to note from this menu
Other things to note from this menu besides just this layers aspect, I can
besides just this layers aspect, I can also go and change the different base
also go and change the different base maps that I have. I could change it into
maps that I have. I could change it into a dark gray canvas instead. And I really
a dark gray canvas instead. And I really liking that. We'll leave it light gray.
liking that. We'll leave it light gray. Then they have other things like a
Then they have other things like a selection tool, a search tool, and then
selection tool, a search tool, and then also do with further analysis. We're not
also do with further analysis. We're not going to go any further into that. I
going to go any further into that. I feel like this is as good as we're going
feel like this is as good as we're going to get with this, and this is all we
to get with this, and this is all we need to know for this type of visual.
need to know for this type of visual. Also, I forgot a title. Where are the
Also, I forgot a title. Where are the highest paying jobs? So, don't forget to
highest paying jobs? So, don't forget to put that in. So, that is an intro into
put that in. So, that is an intro into map visuals. you now have some practice
map visuals. you now have some practice problems to go through and get more
problems to go through and get more familiar with these different maps. In
familiar with these different maps. In our next lesson, we're going to be
our next lesson, we're going to be covering our final portion on different
covering our final portion on different charts you can build in PowerBI. It'll
charts you can build in PowerBI. It'll be focused on uncommon charts. So, it's
be focused on uncommon charts. So, it's going to be rapid pace, basically just
going to be rapid pace, basically just getting you an intro into what maps are
getting you an intro into what maps are also available inside the PowerBI
also available inside the PowerBI service before we move on to other
service before we move on to other greater things like tables, slicers, and
greater things like tables, slicers, and whatnot. With that, I'll see you there.
Welcome to this lesson on uncommon charts. Basically, there's a fitting
charts. Basically, there's a fitting title because we covered common charts.
title because we covered common charts. Now, we're going to cover some uncommon
Now, we're going to cover some uncommon ones. Now, there's actually like a dozen
ones. Now, there's actually like a dozen other charts that we haven't covered
other charts that we haven't covered yet. And actually, I'm going to just
yet. And actually, I'm going to just cover them briefly here at the beginning
cover them briefly here at the beginning so that way you're aware of them, but
so that way you're aware of them, but for this, we're going to be focusing on
for this, we're going to be focusing on three main charts. And well, for that,
three main charts. And well, for that, let's jump into the PowerBI.
let's jump into the PowerBI. Specifically, we're going to be building
Specifically, we're going to be building a ribbon chart and then what's known as
a ribbon chart and then what's known as a waterfall chart. And then finally,
a waterfall chart. And then finally, this bad boy down here is a funnel
this bad boy down here is a funnel chart. These are all pretty easy to
chart. These are all pretty easy to build, so we should be pretty quick to
build, so we should be pretty quick to cover them. Now, going into our
cover them. Now, going into our notebook, let's look at some other uncom
notebook, let's look at some other uncom uncommon types that we're not going to
uncommon types that we're not going to even get into in this video or even for
even get into in this video or even for the remainder of this course. If I go to
the remainder of this course. If I go to the insert tab, I have this section on
the insert tab, I have this section on AI visuals. They have Q&A, key
AI visuals. They have Q&A, key influencers, decomposition tree, and
influencers, decomposition tree, and narrative. You can also access them down
narrative. You can also access them down here in the actual visualization pane.
here in the actual visualization pane. Anyway, these AI features or AI features
Anyway, these AI features or AI features I should put in quotes are really bad
I should put in quotes are really bad and I don't find any use out of them.
and I don't find any use out of them. Here I just click Q&A and let's just
Here I just click Q&A and let's just type in a question that I think it maybe
type in a question that I think it maybe another way on the answer. But it says,
another way on the answer. But it says, "What is the median salary?" Oh, I
"What is the median salary?" Oh, I didn't spell right of data analyst. I'll
didn't spell right of data analyst. I'll go ahead and type that. And yeah, um
go ahead and type that. And yeah, um yeah, it doesn't it doesn't even give us
yeah, it doesn't it doesn't even give us a visual. I cannot stand this Q&A
a visual. I cannot stand this Q&A feature or really any of the AI map
feature or really any of the AI map visuals and so I'm not going to go over
visuals and so I'm not going to go over them and I'm not going to recommend
them and I'm not going to recommend them. Next on this insert tab is power
them. Next on this insert tab is power platforms and this you can create uh
platforms and this you can create uh pageionated reports basically breakdown
pageionated reports basically breakdown of reports that you want to send to
of reports that you want to send to somebody else. You can integrate Power
somebody else. You can integrate Power Apps or even Power Automate. Both Power
Apps or even Power Automate. Both Power Apps and Power Automate are great tools
Apps and Power Automate are great tools to dive into further after this, but
to dive into further after this, but frankly for the basics of PowerBI, it's
frankly for the basics of PowerBI, it's beyond the scope of this. And so we're
beyond the scope of this. And so we're not going to be going into any of this
not going to be going into any of this for this course. And on that note,
for this course. And on that note, related looking down here in the
related looking down here in the visualization pane, they also have
visualization pane, they also have something like the R script visual and
something like the R script visual and the Python script visual. Anyway, if I
the Python script visual. Anyway, if I drag something or I create something
drag something or I create something like a Python visual, yeah, we can put
like a Python visual, yeah, we can put some values in here, but overall, as you
some values in here, but overall, as you can see, you have to be able to write in
can see, you have to be able to write in for Python, you have to be able to write
for Python, you have to be able to write in Python. For R, you have to be able to
in Python. For R, you have to be able to write in R. I'm assuming most of you
write in R. I'm assuming most of you don't have the capabilities to write in
don't have the capabilities to write in Python or R. And I honestly don't use
Python or R. And I honestly don't use Python or R unless I really need to into
Python or R unless I really need to into a PowerBI report. So, not going to
a PowerBI report. So, not going to recommend this either.
And with that, let's get into our first uncommon chart, which is a ribbon chart.
uncommon chart, which is a ribbon chart. Ribbon charts are pretty cool because
Ribbon charts are pretty cool because they show over specifically I like to
they show over specifically I like to use it on a time basis. This is quarter
use it on a time basis. This is quarter down here. Remember, we can use our
down here. Remember, we can use our drill down. I'll drill down one more
drill down. I'll drill down one more into month. You'll be able to see what
into month. You'll be able to see what is the top value over time. That's how
is the top value over time. That's how it's actually sorting it. The lowest
it's actually sorting it. The lowest value is at bottom. I'll be honest, this
value is at bottom. I'll be honest, this one is a little bit of a hot mess. This
one is a little bit of a hot mess. This is a little bit too many values on here.
is a little bit too many values on here. I could make this a little bit more
I could make this a little bit more readable by only having something like
readable by only having something like data scientist, engineer, and scientist
data scientist, engineer, and scientist on here to see what are the top salaries
on here to see what are the top salaries throughout the year. So, let's get into
throughout the year. So, let's get into creating this bad boy. I already started
creating this bad boy. I already started a new page called uncommon charts. You
a new page called uncommon charts. You need to go ahead and do the same. And
need to go ahead and do the same. And inside of here, I'm going to insert in a
inside of here, I'm going to insert in a ribbon chart. Put into that quadrant.
ribbon chart. Put into that quadrant. And I'm going to go into focus mode. For
And I'm going to go into focus mode. For the x-axis, I'm going to go ahead and
the x-axis, I'm going to go ahead and use a time series data. So, we're going
use a time series data. So, we're going to use that job posted date. Right now,
to use that job posted date. Right now, it's filtered to year. So remember,
it's filtered to year. So remember, we're going to use all the way to the
we're going to use all the way to the right these this drop down arrow right
right these this drop down arrow right here. And I'm going to go into quarter
here. And I'm going to go into quarter for the time being. Now, as far as the
for the time being. Now, as far as the y-axis, we're going to once again use
y-axis, we're going to once again use that median salary like we've been
that median salary like we've been doing. Change this from sum to median
doing. Change this from sum to median and rename this to median yearly salary
and rename this to median yearly salary USD. So now we can see even with just
USD. So now we can see even with just this, we can see that yeah, over the
this, we can see that yeah, over the year, oh, median salary has gone up
year, oh, median salary has gone up slightly. But now we want to break it
slightly. But now we want to break it down based on the job titles themselves.
down based on the job titles themselves. So, we'll take that job title short,
So, we'll take that job title short, throw it into the legend, change that to
throw it into the legend, change that to job title, and then bam, we can see over
job title, and then bam, we can see over the year what has happened here. It
the year what has happened here. It looks like senior data scientist came
looks like senior data scientist came out of top the end of the year with
out of top the end of the year with $152,000.
$152,000. Now, like I mentioned before, I'm not
Now, like I mentioned before, I'm not really a fan of this. I would probably
really a fan of this. I would probably more likely recommend something like a
more likely recommend something like a line chart for this. Although, even with
line chart for this. Although, even with this, there's just way too many lines on
this, there's just way too many lines on here. So, I'd probably want to filter it
here. So, I'd probably want to filter it down with the number of jobs that it has
down with the number of jobs that it has in here. But line chart, it's going to
in here. But line chart, it's going to be my preference over something like a
be my preference over something like a ribbon chart.
Next up is a waterfall chart. And it gets its name because it kind of looks
gets its name because it kind of looks like it goes step to step to step kind
like it goes step to step to step kind of like a waterfall does. But the point
of like a waterfall does. But the point of this type of visualization is to show
of this type of visualization is to show how portions of a final value are made
how portions of a final value are made up of things that can add and subtract
up of things that can add and subtract from it. In this case, we're showing
from it. In this case, we're showing what is based on the total salary for a
what is based on the total salary for a data analyst salary breakdown. This
data analyst salary breakdown. This darker blue bar is what they're getting
darker blue bar is what they're getting at the end. So, $80,000. And then as it
at the end. So, $80,000. And then as it goes through these lighter blue are the
goes through these lighter blue are the different things that add to the salary
different things that add to the salary and this uh gray is things that subtract
and this uh gray is things that subtract from the salary giving us our final
from the salary giving us our final total. This type of visualization is
total. This type of visualization is very common in financial roles. Now if
very common in financial roles. Now if you recall from our data we don't have
you recall from our data we don't have it in a manner actually we just need to
it in a manner actually we just need to go to table view. We don't have any data
go to table view. We don't have any data especially numerical data in a in a
especially numerical data in a in a format that's necessary to actually make
format that's necessary to actually make this type of chart. So we need to insert
this type of chart. So we need to insert some data in to create a chart like
some data in to create a chart like this. Back in the home tab I'm going to
this. Back in the home tab I'm going to go in and we're going to enter data.
go in and we're going to enter data. We're going to ahead and insert some
We're going to ahead and insert some values into here. Specifically for base
values into here. Specifically for base salary we'll say it starts at 75,000.
salary we'll say it starts at 75,000. Bonus is at 5,000. Stock options are at
Bonus is at 5,000. Stock options are at 7,000. Not too shabby. Benefit values is
7,000. Not too shabby. Benefit values is at 8,000. Taxes induction at -15,000.
at 8,000. Taxes induction at -15,000. I'm going to change these column names
I'm going to change these column names by double clicking on it. This will be
by double clicking on it. This will be the column of comp. This will be of
the column of comp. This will be of amount. I'm using this for our waterfall
amount. I'm using this for our waterfall chart. So, I'll just call this waterfall
chart. So, I'll just call this waterfall data. We'll go ahead and load this in.
data. We'll go ahead and load this in. Inside the data pane, I can see that
Inside the data pane, I can see that it's appearing now with a mountain comp.
it's appearing now with a mountain comp. I can also go into the table view.
I can also go into the table view. Selecting that table, we can see that
Selecting that table, we can see that it's in there. So, let's go ahead and
it's in there. So, let's go ahead and insert in that waterfall chart, going to
insert in that waterfall chart, going to put in that top quadrant. For the
put in that top quadrant. For the category, I'm going to go ahead and drag
category, I'm going to go ahead and drag in comp. And then we're not going to use
in comp. And then we're not going to use breakdown because I want to break down
breakdown because I want to break down any further. We're going to use the
any further. We're going to use the yaxis specifically. We'll drag in that
yaxis specifically. We'll drag in that for this. Right now, we'll just put it a
for this. Right now, we'll just put it a sum. These individual values could be
sum. These individual values could be broken down more, maybe with another
broken down more, maybe with another column, but that's beyond the scope of
column, but that's beyond the scope of this. We're not going to do it. We're
this. We're not going to do it. We're going to keep this simple. I'm going to
going to keep this simple. I'm going to open this up into focus mode. And the
open this up into focus mode. And the main thing that stands out to me is the
main thing that stands out to me is the coloring. Once again, I'm not a big fan
coloring. Once again, I'm not a big fan of different colorings. I do like that
of different colorings. I do like that the aspect of they're doing green for
the aspect of they're doing green for positive values, red for negative, and
positive values, red for negative, and blue for the final, but still that's
blue for the final, but still that's just too much in my opinion. So, I'm
just too much in my opinion. So, I'm going to go to format your visual and
going to go to format your visual and underneath here. I'm trying to find out
underneath here. I'm trying to find out where I can change the color. A little
where I can change the color. A little shortcut is I'm going to use the search
shortcut is I'm going to use the search bar up here and just type color. I'm
bar up here and just type color. I'm going scroll down until I find the
going scroll down until I find the colors that I wanted. Oh, there it is.
colors that I wanted. Oh, there it is. That's what I want to change right here.
That's what I want to change right here. For increase, I'm going to make it a
For increase, I'm going to make it a light blue. For decrease, I'm going to
light blue. For decrease, I'm going to make it a dark gray. And then for the
make it a dark gray. And then for the total, I'm just going to change it to
total, I'm just going to change it to this dark blue. All right. So, bam,
this dark blue. All right. So, bam, that's a waterfall chart. And like I
that's a waterfall chart. And like I mentioned, this is has a lot of
mentioned, this is has a lot of negatives to it in the fact that you
negatives to it in the fact that you usually don't get data that's in this
usually don't get data that's in this format. So, you need to use something
format. So, you need to use something like Power Query, which is going to be
like Power Query, which is going to be in the next chapter, in order to clean
in the next chapter, in order to clean data up and get it into this type of
data up and get it into this type of format. Makes an entire hassle.
Last one to cover is a funnel chart. And similar to the last chart, you have to
similar to the last chart, you have to have the data in a certain format in
have the data in a certain format in order to feed it in and actually be able
order to feed it in and actually be able to make or reconcile what's going on
to make or reconcile what's going on here. Anyway, the point of this this
here. Anyway, the point of this this funnel is to show how people or whatever
funnel is to show how people or whatever it may be goes through a funnel process.
it may be goes through a funnel process. So, in this case, this is job applicants
So, in this case, this is job applicants per stage. They those that view the
per stage. They those that view the posting is around 5,000. Those that
posting is around 5,000. Those that clicked apply, it was around 4K. started
clicked apply, it was around 4K. started the application around 3K, submitted 2K,
the application around 3K, submitted 2K, interviewed 1K, and hired 0K, which
interviewed 1K, and hired 0K, which going over the toolkit, looks like it's
going over the toolkit, looks like it's around 120. So, only 2.4% out of this
around 120. So, only 2.4% out of this 100% got into getting a job. That's what
100% got into getting a job. That's what funnel charts are great at showing. So,
funnel charts are great at showing. So, let's create this real quick. We're
let's create this real quick. We're going to throw in a funnel chart. Put
going to throw in a funnel chart. Put into focus mode. And we don't have any
into focus mode. And we don't have any data. We just need to enter that data.
data. We just need to enter that data. We'll put in first the value of view job
We'll put in first the value of view job postings at 5,000. clicked apply at
postings at 5,000. clicked apply at 3,800, started application at 2,900,
3,800, started application at 2,900, submitted at 2,200, interviewed at 500,
submitted at 2,200, interviewed at 500, and then hired at 120. We'll label the
and then hired at 120. We'll label the column names as stage, and then
column names as stage, and then applicants. Last thing we'll do is just
applicants. Last thing we'll do is just need to make sure we update the uh the
need to make sure we update the uh the table name, and then change it to funnel
table name, and then change it to funnel data. We'll go ahead and click load.
data. We'll go ahead and click load. Now, with our funnel data, I'm going to
Now, with our funnel data, I'm going to drag applicants or sorry, I'm going to
drag applicants or sorry, I'm going to drag stage into the category and then
drag stage into the category and then applicants into the values. Now, one
applicants into the values. Now, one thing I didn't like from last time is
thing I didn't like from last time is how it goes 54321 and then 0. Okay, that
how it goes 54321 and then 0. Okay, that I don't feel like that's descriptive
I don't feel like that's descriptive enough. So, under format your visual,
enough. So, under format your visual, I'm not even going to search for it. I'm
I'm not even going to search for it. I'm just going to search and I'm going to
just going to search and I'm going to type decimal. And we have value decimal
type decimal. And we have value decimal places. I'm going to put this as zero or
places. I'm going to put this as zero or sorry, not zero. We're going to put as
sorry, not zero. We're going to put as one. So, now this shows more of a
one. So, now this shows more of a breakdown of what's going on here. so we
breakdown of what's going on here. so we can actually see what's going on. And
can actually see what's going on. And that's the one thing I'm going to change
that's the one thing I'm going to change with this.
All right, one bonus section that I do want to add into this and that is on get
want to add into this and that is on get more visuals. What do I mean by that?
more visuals. What do I mean by that? Well, if you notice, we have these
Well, if you notice, we have these ellipses down here at the bottom of the
ellipses down here at the bottom of the visualization pane and it says, hey, get
visualization pane and it says, hey, get more visuals. I'm going to go ahead and
more visuals. I'm going to go ahead and click it and I can say I can import it
click it and I can say I can import it from file, remove visual, what not. Here
from file, remove visual, what not. Here I want to get more visuals. Now, this is
I want to get more visuals. Now, this is going to pop up and show us some
going to pop up and show us some different ways we can get other visuals.
different ways we can get other visuals. I'm going to go back real quick and call
I'm going to go back real quick and call out something. You may try this. If
out something. You may try this. If you're not logged in, if you don't have
you're not logged in, if you don't have an account, you don't you can't you're
an account, you don't you can't you're not signed in, you're not going to be
not signed in, you're not going to be able to go through and get more visuals
able to go through and get more visuals without actually signing in. If you're
without actually signing in. If you're not able to do that, don't worry about
not able to do that, don't worry about it. Not a big deal. We have some
it. Not a big deal. We have some practice problems using these, but I've
practice problems using these, but I've made them optional, so you don't need to
made them optional, so you don't need to necessarily do them. But I'm going to
necessarily do them. But I'm going to just go through and showcase what is
just go through and showcase what is capable what you're able to do with
capable what you're able to do with this. Anyway, we're going to go ahead
this. Anyway, we're going to go ahead and search for something specifically
and search for something specifically box and whisker chart. And it's good
box and whisker chart. And it's good whenever you're looking at any of these
whenever you're looking at any of these that you look at the ratings and that at
that you look at the ratings and that at least does have some ratings. This one
least does have some ratings. This one doesn't have any ratings. Makes me
doesn't have any ratings. Makes me question it. I've tried this one from
question it. I've tried this one from data scenarios. So, we're going to go
data scenarios. So, we're going to go with that. Now, for this, I have the
with that. Now, for this, I have the ability to now add this. I do want to
ability to now add this. I do want to call something out real quick. If I go
call something out real quick. If I go back, if I go into this other one, Box
back, if I go into this other one, Box and Whiskers Pro, they actually have
and Whiskers Pro, they actually have underneath it plans and pricings. And
underneath it plans and pricings. And you can get into some where depending on
you can get into some where depending on the users and where you want to publish
the users and where you want to publish it, but they are going to charge you for
it, but they are going to charge you for this. So, be careful of which ones you
this. So, be careful of which ones you choose if you want to get it charged or
choose if you want to get it charged or not. You'd have to enter in your credit
not. You'd have to enter in your credit card to do all that kind of stuff. So,
card to do all that kind of stuff. So, you're not going to get charged without
you're not going to get charged without knowing it, but it may come at a cost.
knowing it, but it may come at a cost. They may not display it unless you're
They may not display it unless you're paying. Anyway, I want this one. I'm
paying. Anyway, I want this one. I'm going to go ahead and click add. Now we
going to go ahead and click add. Now we notice uh underneath the divider here we
notice uh underneath the divider here we now have this box and whiskers chart
now have this box and whiskers chart which is a new one that we have
which is a new one that we have available. I put job title short into
available. I put job title short into the category and then put salary year
the category and then put salary year average into the sampling we want for
average into the sampling we want for this and salary average into the values
this and salary average into the values specifically. I don't want sum, I want
specifically. I don't want sum, I want the median. And then open this bad boy
the median. And then open this bad boy up so we can see it. Bam. Now I have a
up so we can see it. Bam. Now I have a visualization that was not previously
visualization that was not previously accessible to me via the standard ones
accessible to me via the standard ones in here and I can actually visualize
in here and I can actually visualize something for free. Pretty neat. Now I
something for free. Pretty neat. Now I have noticed with a lot of these the
have noticed with a lot of these the customization that you can actually do
customization that you can actually do with this. Yeah, there is a lot of
with this. Yeah, there is a lot of options. I'm not going to go into
options. I'm not going to go into customizing this one. The customization
customizing this one. The customization can get kind of limited and they can
can get kind of limited and they can sometimes be buggy because they're not
sometimes be buggy because they're not officially PowerBI approved all the
officially PowerBI approved all the time. So that is something to think in
time. So that is something to think in mind whenever you decide to go out and
mind whenever you decide to go out and get a visualization within the get more
get a visualization within the get more visuals. All right, it's now your turn
visuals. All right, it's now your turn to go through and build some of these
to go through and build some of these uncommon charts. We actually have some
uncommon charts. We actually have some practice problems as well that include
practice problems as well that include price problems on get more visuals if
price problems on get more visuals if you want to get experience with that.
you want to get experience with that. Once again, those portions of the
Once again, those portions of the practice problems will be optional
practice problems will be optional because you do have to have an account
because you do have to have an account login to sign in. So don't worry if you
login to sign in. So don't worry if you can't accomplish it. In the next lesson,
can't accomplish it. In the next lesson, we're going to be jumping into tables
we're going to be jumping into tables and matrices. With that, I'll see you
and matrices. With that, I'll see you there.
In this video, we're going to be covering tables and also matrices. And
covering tables and also matrices. And especially if you have end users like
especially if you have end users like your boss, maybe that's more familiar
your boss, maybe that's more familiar with something like Excel. They're going
with something like Excel. They're going to from time to time request that you
to from time to time request that you put stuff into tables. Anyway, jumping
put stuff into tables. Anyway, jumping into the PowerBI file to show what we're
into the PowerBI file to show what we're going to be doing in this lesson. As we
going to be doing in this lesson. As we can see from that homepage, we've
can see from that homepage, we've covered everything we're going to cover
covered everything we're going to cover for charts. We're now on to other
for charts. We're now on to other visuals. for right now we're covering
visuals. for right now we're covering tables. Then we'll cover cards and next
tables. Then we'll cover cards and next slicers. Anyway, let's go into tables.
slicers. Anyway, let's go into tables. We're going to be building this table
We're going to be building this table which aggregates all the different key
which aggregates all the different key information from job postings that
information from job postings that contain a yearly salary. Tables are
contain a yearly salary. Tables are pretty nice cuz I can click on the
pretty nice cuz I can click on the different columns and I can sort them
different columns and I can sort them depending on what value is where. And we
depending on what value is where. And we can see something like this. We're data
can see something like this. We're data scientists at Netflix. We're getting
scientists at Netflix. We're getting $920,000.
$920,000. Gosh, full-time job. Anyway, we're also
Gosh, full-time job. Anyway, we're also going to be going through not just this
going to be going through not just this uh how to make the table itself, but
uh how to make the table itself, but also conditional formatting. That's what
also conditional formatting. That's what these blue data bars are right here and
these blue data bars are right here and then these icons right here. And we're
then these icons right here. And we're going to be using some quick measures to
going to be using some quick measures to make these stars. Now, after we cover
make these stars. Now, after we cover tables, we're going to go into matrices.
tables, we're going to go into matrices. If you're familiar with pivot tables in
If you're familiar with pivot tables in Excel, that's basically what this is.
Excel, that's basically what this is. This is allows us to do aggregation
This is allows us to do aggregation on certain columns. In this case, we're
on certain columns. In this case, we're going to do aggregation on the job title
going to do aggregation on the job title short column to see things like salary
short column to see things like salary and count. We can also have hierarchies
and count. We can also have hierarchies within it. In this case, I can go dive
within it. In this case, I can go dive into business analyst and I can look at
into business analyst and I can look at it in the different quarters as it
it in the different quarters as it progresses along. I use conditional
progresses along. I use conditional formatting for the bars. And then over
formatting for the bars. And then over here on the right hand side, we have job
here on the right hand side, we have job trends, which is using spark lines,
trends, which is using spark lines, which is the last thing we're actually
which is the last thing we're actually going to cover for this.
going to cover for this. So, let's start with creating this
So, let's start with creating this table. I'm going to come into create a
table. I'm going to come into create a blank page. I'm going to rename it.
blank page. I'm going to rename it. Actually, call it something creative
Actually, call it something creative like tables. And inside of here, I'm
like tables. And inside of here, I'm going to come in here and select the
going to come in here and select the table icon. We're going to extend it all
table icon. We're going to extend it all the way over and make it in the top
the way over and make it in the top half. Now, there's only one field well
half. Now, there's only one field well here, and that's the add data fields
here, and that's the add data fields right here for columns. So, we can come
right here for columns. So, we can come in here and start dragging things in.
in here and start dragging things in. We're going to start with just the job
We're going to start with just the job title short column, which shows those 10
title short column, which shows those 10 values. And then I actually want to see
values. And then I actually want to see what is the full job title. So, I'm
what is the full job title. So, I'm going to drag that next into here. After
going to drag that next into here. After this, I want the company information.
this, I want the company information. So, I'm put in company name. I want the
So, I'm put in company name. I want the salary information. So, we'll drag in
salary information. So, we'll drag in salary year average. Right now, it's
salary year average. Right now, it's doing aggregation. We'll fix that in a
doing aggregation. We'll fix that in a second. And then finally, the last
second. And then finally, the last column that we're going to drag in for
column that we're going to drag in for the time being is that job schedule
the time being is that job schedule type. Okay, getting back to that sum of
type. Okay, getting back to that sum of salary. We don't want to necessarily do
salary. We don't want to necessarily do a sum. There are some cases like this.
a sum. There are some cases like this. Oh my gosh, I can't even see this. I'm
Oh my gosh, I can't even see this. I'm going to open up the focus mode. There
going to open up the focus mode. There are this case where it is doing a sum
are this case where it is doing a sum and that's because there's multiple jobs
and that's because there's multiple jobs that fit this job title and company
that fit this job title and company name. So it sums up all the sellers. I
name. So it sums up all the sellers. I don't want to do an aggregation. So I'm
don't want to do an aggregation. So I'm going to click this down arrow right
going to click this down arrow right here and I'm going to say don't
here and I'm going to say don't summarize it. Now I'm going to go back
summarize it. Now I'm going to go back into the report so we can actually see
into the report so we can actually see it. All right, not too bad. I do have a
it. All right, not too bad. I do have a bunch of blank values for salary or
bunch of blank values for salary or average. I just want to see the postings
average. I just want to see the postings that have a yearly salary associated
that have a yearly salary associated with it. So, going into the filters pane
with it. So, going into the filters pane under salary year average, I'm going to
under salary year average, I'm going to say show items when the value is not
say show items when the value is not blank. And let's see if this works. Bam.
blank. And let's see if this works. Bam. Does work. Now, we're getting a bunch of
Does work. Now, we're getting a bunch of salary values in there. Okay, let's go
salary values in there. Okay, let's go back into focus mode and do some just
back into focus mode and do some just final cleanup. I'm going to adjust this
final cleanup. I'm going to adjust this column right here so we can see all
column right here so we can see all them. We need to adjust all these
them. We need to adjust all these different column titles and update to
different column titles and update to make it look a little more readable. Job
make it look a little more readable. Job title, job title, full, company, yearly
title, job title, full, company, yearly salary, and job type. Not too bad. Now,
salary, and job type. Not too bad. Now, with something like this, it's important
with something like this, it's important to understand if I put this in to a
to understand if I put this in to a visual and somebody wanted access to
visual and somebody wanted access to this data, remember, they can go to
this data, remember, they can go to those more options and then export the
those more options and then export the data and then they wanted it, they could
data and then they wanted it, they could have it in something like Excel and if
have it in something like Excel and if they're more of a master of it, they can
they're more of a master of it, they can use it there.
use it there. All right, let's get back to our table.
All right, let's get back to our table. There's one thing I want to do to this
There's one thing I want to do to this to spice it up. not necessarily
to spice it up. not necessarily conditional formatting just yet, but
conditional formatting just yet, but instead looking at what our final table
instead looking at what our final table is, I want to add these stars in here
is, I want to add these stars in here and be able to showcase based on a
and be able to showcase based on a certain salary, if it meets my salary,
certain salary, if it meets my salary, it being five stars, and then down to
it being five stars, and then down to zero stars. Now, in order to do this,
zero stars. Now, in order to do this, back in our table, I'm going to go to
back in our table, I'm going to go to that modeling tab, and what we're going
that modeling tab, and what we're going to use is a quick measure. Now, measures
to use is a quick measure. Now, measures in general, remember, we're going to go
in general, remember, we're going to go really in detail in it in chapter 4, but
really in detail in it in chapter 4, but this we're going to give a sneak peek
this we're going to give a sneak peek and see in the capabilities of something
and see in the capabilities of something like quick measures, which honestly
like quick measures, which honestly we're going to come to find out it's
we're going to come to find out it's quite limited. These quick measures
quite limited. These quick measures generate DAX in order to satisfy our
generate DAX in order to satisfy our need. So, we could do things like
need. So, we could do things like aggregation, filtering, time
aggregation, filtering, time intelligence, totals, but I'm want we're
intelligence, totals, but I'm want we're going to go down to this one here of
going to go down to this one here of text and specifically star ratings. The
text and specifically star ratings. The first thing we need to do, it's pretty
first thing we need to do, it's pretty self-intuitive. We need a base value,
self-intuitive. We need a base value, and this is the value want to convert
and this is the value want to convert into a star rating. Remember, we're
into a star rating. Remember, we're going to be using this from that salary
going to be using this from that salary year average column. We want to base it
year average column. We want to base it off of that. So, I'm going to drag it
off of that. So, I'm going to drag it into add data. We don't want this to be
into add data. We don't want this to be sum, right? We want this to be median.
sum, right? We want this to be median. So, I'm going to go ahead and change
So, I'm going to go ahead and change this underneath here. And now we can do
this underneath here. And now we can do there. It's going to provide what are
there. It's going to provide what are the number of stars we want and we want
the number of stars we want and we want what is the value for the lowest star
what is the value for the lowest star rating. Well, I'm going to say, hey, my
rating. Well, I'm going to say, hey, my lowest point that I want to give a star
lowest point that I want to give a star for any star for, I'm going to say let's
for any star for, I'm going to say let's say 75,000. And then something that
say 75,000. And then something that would exceed my expectations in salary,
would exceed my expectations in salary, I'm going to give that of 150,000. So,
I'm going to give that of 150,000. So, I'm going go ahead and click add. And as
I'm going go ahead and click add. And as we can see, I'm going to uh hide this
we can see, I'm going to uh hide this off to the side. It generated all the
off to the side. It generated all the different DAXs necessary. This is up in
different DAXs necessary. This is up in the formula bar up at the top and
the formula bar up at the top and conveniently it ended up putting it into
conveniently it ended up putting it into or unconveniently it ended up putting it
or unconveniently it ended up putting it into our funnel data table. Now this is
into our funnel data table. Now this is actually we don't I don't want in the
actually we don't I don't want in the funnel data table and also need to
funnel data table and also need to change its name. So we'll do both of
change its name. So we'll do both of those things. First is I want to change
those things. First is I want to change the home table to job posting flat and
the home table to job posting flat and then the name up here to salary star
then the name up here to salary star rating. If you notice it updated in the
rating. If you notice it updated in the formula. All right. All right, I'm going
formula. All right. All right, I'm going to go ahead and close out of that
to go ahead and close out of that formula. Click into here. Now, for this
formula. Click into here. Now, for this table, we want to add that in. So, I'm
table, we want to add that in. So, I'm going to take this salary star rating as
going to take this salary star rating as designated by this measures icon next to
designated by this measures icon next to it. We're going to drag it and put it
it. We're going to drag it and put it right in that first column. Opening up
right in that first column. Opening up focus mode so we can actually see what's
focus mode so we can actually see what's going on here. And adjusting the column
going on here. And adjusting the column so we can actually read it. Okay, this
so we can actually read it. Okay, this is looking like it's working. So,
is looking like it's working. So, something like 32,000 doesn't get any
something like 32,000 doesn't get any stars. whereas something like 163,000
stars. whereas something like 163,000 does get five stars because it's above
does get five stars because it's above that 150,000. Anyway, I really like the
that 150,000. Anyway, I really like the star rating, especially that quick
star rating, especially that quick measure. It makes it quick and easy to
measure. It makes it quick and easy to create a measure like this.
create a measure like this. Unfortunately, going back to quick
Unfortunately, going back to quick measures and looking at it, honestly, I
measures and looking at it, honestly, I don't get a lot of value out of any of
don't get a lot of value out of any of these other ones. I've tried to use it
these other ones. I've tried to use it before with the exception of this. And
before with the exception of this. And really, I get more value out of writing
really, I get more value out of writing my own DAX to create measures, which
my own DAX to create measures, which like I said, we're going to go into it
like I said, we're going to go into it more in chapter 4. So, just stay tuned
more in chapter 4. So, just stay tuned for that.
for that. Next, let's get into building our
Next, let's get into building our matrix. And with this, very similar in
matrix. And with this, very similar in format in that we want to do aggregation
format in that we want to do aggregation of the job titles, but we're going to do
of the job titles, but we're going to do finding that of count and then also the
finding that of count and then also the different hourly and median salaries.
different hourly and median salaries. We're not going to be inserting in the
We're not going to be inserting in the trend lines just yet or the conditional
trend lines just yet or the conditional formatting. We'll be doing that after we
formatting. We'll be doing that after we set up the um matrix. So, inside of our
set up the um matrix. So, inside of our canvas, I'm going to go ahead and insert
canvas, I'm going to go ahead and insert in a matrix. I'm going put the job title
in a matrix. I'm going put the job title short into the rows. And then they have
short into the rows. And then they have columns, but really we're going to want
columns, but really we're going to want to do values. But let me just show you
to do values. But let me just show you what's going on with this uh for I could
what's going on with this uh for I could put something like columns, the job
put something like columns, the job countries in the columns. And then let's
countries in the columns. And then let's say I wanted like the count, which we
say I wanted like the count, which we are going to keep. So, I'm going to drag
are going to keep. So, I'm going to drag job tile short to the values. And we're
job tile short to the values. And we're going to do count here. Now we have
going to do count here. Now we have based on this right columns are along or
based on this right columns are along or the countries rows are the job tile
the countries rows are the job tile short. And then inside of here we have
short. And then inside of here we have all the different counts depending on
all the different counts depending on the country with something as much as
the country with something as much as country and how wide this table is. Now
country and how wide this table is. Now not finding much use out of that. So I'm
not finding much use out of that. So I'm actually going to just remove job
actually going to just remove job country. And we still have that job
country. And we still have that job count in there. Other values we want to
count in there. Other values we want to drag into there are that yearly salary
drag into there are that yearly salary and hourly salary. adjusting them both
and hourly salary. adjusting them both to be those median values. Then I'm
to be those median values. Then I'm going to go ahead and put this into into
going to go ahead and put this into into focus mode and then also cleaned up all
focus mode and then also cleaned up all the columns to job title, job count,
the columns to job title, job count, yearly salary, and hourly salary. Now
yearly salary, and hourly salary. Now remember, right, this is a matrix. So we
remember, right, this is a matrix. So we can create a hierarchy within here. And
can create a hierarchy within here. And as we did previously, I use the, as I
as we did previously, I use the, as I showed previously, I've used the
showed previously, I've used the quarter. So I'm actually going to grab
quarter. So I'm actually going to grab quarter within underneath job posted
quarter within underneath job posted date. I'm going drag it into the rows.
date. I'm going drag it into the rows. Now, for this expand icon right here, I
Now, for this expand icon right here, I can see based on a quarter how it breaks
can see based on a quarter how it breaks down. Some quick formatting things to
down. Some quick formatting things to note on this matrix. What we can also do
note on this matrix. What we can also do going into format visual and then under
going into format visual and then under visual, you can change things like the
visual, you can change things like the subtotals. In this case, it's only
subtotals. In this case, it's only giving us column sub totals or sorry,
giving us column sub totals or sorry, row subtotals. So, I can toggle it on
row subtotals. So, I can toggle it on and off what I want it. This case, it's
and off what I want it. This case, it's not going to give us those column sub
not going to give us those column sub totals. The other thing is what happens
totals. The other thing is what happens if we want to format these numbers
if we want to format these numbers further. Let's take specifically the job
further. Let's take specifically the job count. So I can go down here to specific
count. So I can go down here to specific column have job count selected. And then
column have job count selected. And then underneath values we can actually change
underneath values we can actually change the display units that we want cuz right
the display units that we want cuz right now 12,000 or 128,994 that's kind of
now 12,000 or 128,994 that's kind of unreadable. So what I can do is I can
unreadable. So what I can do is I can change that to thousands and then for
change that to thousands and then for the decimal place put in a zero.
the decimal place put in a zero. Similarly, I can do the same for
Similarly, I can do the same for something like the yearly salary as
something like the yearly salary as well. I could change that to thousands.
well. I could change that to thousands. And then that one's also more readable.
And then that one's also more readable. For hourly salary, I'm not getting much
For hourly salary, I'm not getting much value out of those two decimal places.
value out of those two decimal places. So, we're just going to change that to
So, we're just going to change that to zero. Bam. Much more readable the data
zero. Bam. Much more readable the data that's coming out of this. Now, with
that's coming out of this. Now, with these matrices, right, especially since
these matrices, right, especially since we did that hierarchy of the quarter
we did that hierarchy of the quarter underneath here, you also have these
underneath here, you also have these drill downs up here for you to drill
drill downs up here for you to drill down into. And if you wanted to, you can
down into. And if you wanted to, you can expand all the way down by using the
expand all the way down by using the navigation up there in the top right
navigation up there in the top right hand corner. Overall, I like to usually
hand corner. Overall, I like to usually just dive into one myself and then dive
just dive into one myself and then dive further as necessary.
Next, let's get into some conditional formatting to spice these visuals up and
formatting to spice these visuals up and draw people's attention to where we want
draw people's attention to where we want them to actually look for this. We're
them to actually look for this. We're going to start with our matrix first,
going to start with our matrix first, and I want to do job count. What we're
and I want to do job count. What we're going to do is click this do uh down
going to do is click this do uh down arrow. And you notice right here we have
arrow. And you notice right here we have conditional formatting. There's a few
conditional formatting. There's a few options. Background color, font color,
options. Background color, font color, data bars, icons, and web URL. Let's
data bars, icons, and web URL. Let's start with background color first. Now,
start with background color first. Now, we can get it to do based on a rule. I'm
we can get it to do based on a rule. I'm typically not a fan actually rules of
typically not a fan actually rules of like, hey, set it at with this value be
like, hey, set it at with this value be a certain color. Instead, I'm going to
a certain color. Instead, I'm going to go to this of gradient, and it
go to this of gradient, and it automatically picks up that we're doing
automatically picks up that we're doing a count of the job title. And it's
a count of the job title. And it's setting the lowest value at this light
setting the lowest value at this light blue and this other one the maximum at a
blue and this other one the maximum at a darker blue. Kind of like it. We'll go
darker blue. Kind of like it. We'll go with it. And bam. Key things to think
with it. And bam. Key things to think about though when you use these blue
about though when you use these blue type colors. I'll be honest, it's a
type colors. I'll be honest, it's a little bit harder to read the numbers
little bit harder to read the numbers that's going on right here. So if I
that's going on right here. So if I want, I can go back into conditional
want, I can go back into conditional formatting for that background color and
formatting for that background color and change this to be slightly less dark.
change this to be slightly less dark. And I think the numbers are a little
And I think the numbers are a little more readable in that matter. All right.
more readable in that matter. All right. Next one to notice for the conditional
Next one to notice for the conditional formatting. We'll go to yearly salatary
formatting. We'll go to yearly salatary conditional formatting. We're going to
conditional formatting. We're going to be doing we'll skip font colors for now.
be doing we'll skip font colors for now. We're going to go to data bars. In this
We're going to go to data bars. In this the format style is data bars. And so
the format style is data bars. And so the only option available available.
the only option available available. We're already doing the median yearly
We're already doing the median yearly salary for this. And in it they have we
salary for this. And in it they have we can specify basically the color. So
can specify basically the color. So positive bars are this blue. Negative
positive bars are this blue. Negative bars you can make if you want it to be
bars you can make if you want it to be red and the axis black. What I'm going
red and the axis black. What I'm going to do, it's all our values are positive.
to do, it's all our values are positive. So, I'm going to go ahead and just
So, I'm going to go ahead and just adjust this to a lighter blue color so
adjust this to a lighter blue color so that way we can still read those numbers
that way we can still read those numbers behind it. Click okay. And bam, we get
behind it. Click okay. And bam, we get this. I think it's still a little too
this. I think it's still a little too dark. Unfortunately, we have to go back
dark. Unfortunately, we have to go back in all the way to data bars and then
in all the way to data bars and then select the color I want. I'm going to do
select the color I want. I'm going to do this light blue one. Click okay. All
this light blue one. Click okay. All right. That's a lot more readable. I'm
right. That's a lot more readable. I'm also going to go through and do this
also going to go through and do this real quick for the hourly column as
real quick for the hourly column as well. Making it at that light blue. then
well. Making it at that light blue. then applying it. Bam. Looks good. This is
applying it. Bam. Looks good. This is all we can do for this matrix. So, let's
all we can do for this matrix. So, let's switch on over to our table. I went to
switch on over to our table. I went to focus mode. So, let's start with that
focus mode. So, let's start with that year yearly salary. We're going to
year yearly salary. We're going to eventually put data bars, but I just
eventually put data bars, but I just want to show conditional formatting. We
want to show conditional formatting. We could do something like a font color
could do something like a font color where it does a gradient from where it
where it does a gradient from where it needs to go and where it needs to be.
needs to go and where it needs to be. Overall font color. I know the coloring
Overall font color. I know the coloring is probably pretty bad on this. In
is probably pretty bad on this. In general, I don't I don't get a lot of
general, I don't I don't get a lot of value at font color, so I don't use that
value at font color, so I don't use that very often. So, what I'll do is I'll
very often. So, what I'll do is I'll open it up. go to remove conditional
open it up. go to remove conditional formatting and we'll select remove font
formatting and we'll select remove font coloring and go back in to add that
coloring and go back in to add that conditional formatting for data bars
conditional formatting for data bars specifying that that positive bar we
specifying that that positive bar we want that that light blue color. All
want that that light blue color. All right, the next thing with this let's
right, the next thing with this let's give it some icons specifically
give it some icons specifically depending on a job type that I'm trying
depending on a job type that I'm trying to get to or that I want maybe I want to
to get to or that I want maybe I want to be able to signify via an icon to cue my
be able to signify via an icon to cue my eyes into it. So I'll go to job type go
eyes into it. So I'll go to job type go into conditional formatting and for this
into conditional formatting and for this one select icons. Right now the format
one select icons. Right now the format that style that's using is rules and so
that style that's using is rules and so that's why it's using the is whatever
that's why it's using the is whatever text and then assigning it a certain
text and then assigning it a certain icon. We can specify we can specify
icon. We can specify we can specify where we want the icon left of data icon
where we want the icon left of data icon only or right of data. Right now we'll
only or right of data. Right now we'll just leave it left of data. And you can
just leave it left of data. And you can even change the type. They have a few
even change the type. They have a few different options you can choose from.
different options you can choose from. We're going to end up changing it to
We're going to end up changing it to we're going to change it to this one
we're going to change it to this one right here with these circles and these
right here with these circles and these up and downs. Basically, I want it to be
up and downs. Basically, I want it to be green whenever if value is. In our case,
green whenever if value is. In our case, I want it to be uh when it's full-time.
I want it to be uh when it's full-time. Part-time will be a yellow. I'm not
Part-time will be a yellow. I'm not really a fan of it. And then red will be
really a fan of it. And then red will be I don't want to I don't even want to
I don't want to I don't even want to look at it. That will be for jobs that
look at it. That will be for jobs that are contractors. Go ahead and click
are contractors. Go ahead and click okay. And now we got visual indications
okay. And now we got visual indications of the different types of jobs along
of the different types of jobs along with this. Now, there's one other type
with this. Now, there's one other type of conditional format we can do, and
of conditional format we can do, and that's with web URLs. And we're actually
that's with web URLs. And we're actually going to get to that in our practice
going to get to that in our practice problems. So for those that supported
problems. So for those that supported the course, you're going to get to that
the course, you're going to get to that eventually.
All right, the last thing we want to do is add a spark line. And that's what
is add a spark line. And that's what this is at the end of this that shows
this is at the end of this that shows it's called job trends, but it's the
it's called job trends, but it's the count of jobs over time. We can see very
count of jobs over time. We can see very quickly that there's a trend over time
quickly that there's a trend over time where we have this dip down in October,
where we have this dip down in October, November area. Anyway, I like using this
November area. Anyway, I like using this especially in these it's only about 10
especially in these it's only about 10 columns or sorry 10 rows here. Great way
columns or sorry 10 rows here. Great way to use it. But as far as our table, not
to use it. But as far as our table, not really a big fan of using it inside of
really a big fan of using it inside of all these different values. It's sort of
all these different values. It's sort of cumbersome at that point. So inside of
cumbersome at that point. So inside of what we have built some forward, I'm
what we have built some forward, I'm going to go back into focus mode and
going to go back into focus mode and since the matrix is selected, I'm going
since the matrix is selected, I'm going to go to insert. Add a spark line is not
to go to insert. Add a spark line is not grayed out. We can actually add a spark
grayed out. We can actually add a spark line. For this, we're going to do the
line. For this, we're going to do the counts of jobs. Like usual, we're going
counts of jobs. Like usual, we're going to use that job title short column in
to use that job title short column in order to calculate that. So I'll select
order to calculate that. So I'll select job title short count. And then finally,
job title short count. And then finally, we'll also do for that X-axis. We want
we'll also do for that X-axis. We want to do job title short. We'll click
to do job title short. We'll click create. Now I had a brain fart. And I
create. Now I had a brain fart. And I completely set that up wrong. But how
completely set that up wrong. But how can we actually fix that? Well, if we go
can we actually fix that? Well, if we go back down into our fields, specifically
back down into our fields, specifically our value fields, click this down arrow.
our value fields, click this down arrow. I'm going to go into edit spark line for
I'm going to go into edit spark line for the x-axis. Right? We're not using job
the x-axis. Right? We're not using job title short. We want to use that date,
title short. We want to use that date, right? Because we want to see it over
right? Because we want to see it over time. Specifically, I don't want all the
time. Specifically, I don't want all the different days. So, I'm going to go into
different days. So, I'm going to go into date hierarchy and I'm going to just
date hierarchy and I'm going to just select month. Click okay. Bam. That's
select month. Click okay. Bam. That's actually what we wanted with this. And
actually what we wanted with this. And I'm going to rename this to job trends.
I'm going to rename this to job trends. If you notice the spark line, it has
If you notice the spark line, it has this sort of trailing arrow similar to
this sort of trailing arrow similar to that spark line up there to signify that
that spark line up there to signify that it is a spark line that we created. Now,
it is a spark line that we created. Now, let's say we wanted to format this spark
let's say we wanted to format this spark line further. I would go into underneath
line further. I would go into underneath format your visual under visual
format your visual under visual scrolling on down all the way to the
scrolling on down all the way to the bottom we have spark lines but the most
bottom we have spark lines but the most important thing is all the way at the
important thing is all the way at the bottom anyway the spark line selected is
bottom anyway the spark line selected is job trends we could change the data
job trends we could change the data color if we want we could also adjust
color if we want we could also adjust the width to be bigger or smaller but
the width to be bigger or smaller but the thing I want to draw attention to is
the thing I want to draw attention to is this next section on markers you could
this next section on markers you could in here mark things like the highest and
in here mark things like the highest and then also the lowest unfortunately they
then also the lowest unfortunately they only have one color option So, if I
only have one color option So, if I wanted to, I could call it the red, but
wanted to, I could call it the red, but then I'm like, which one's highest?
then I'm like, which one's highest? Which one's lowest? Um, because of this,
Which one's lowest? Um, because of this, I'm going to say I'm not going to
I'm going to say I'm not going to actually use it. Fortunately, with
actually use it. Fortunately, with Excel, they give you more fine-tuning
Excel, they give you more fine-tuning capability to give certain colors to
capability to give certain colors to certain values. So, I could find that
certain values. So, I could find that more useful, but in this case, n I'm
more useful, but in this case, n I'm going to leave it off. All right, so not
going to leave it off. All right, so not so bad. We just went through tables and
so bad. We just went through tables and matrices. You have some practice
matrices. You have some practice problems to go through and get familiar
problems to go through and get familiar with how to use these. All right, with
with how to use these. All right, with that, see you in the next one.
In this lesson, we're going to be covering the five different types of
covering the five different types of cards in PowerBI that we can take
cards in PowerBI that we can take advantage of. And these are really
advantage of. And these are really important at displaying key
important at displaying key characteristics about our data. Well,
characteristics about our data. Well, instead of me telling you about it, let
instead of me telling you about it, let me actually show you what I mean. This
me actually show you what I mean. This is our first project that we're going to
is our first project that we're going to be building at the end of this chapter.
be building at the end of this chapter. We don't need to go too much into it,
We don't need to go too much into it, but the key thing here is these are
but the key thing here is these are cards up at the top of the dashboard.
cards up at the top of the dashboard. That's where cards typically located
That's where cards typically located are. These are the key information that
are. These are the key information that we want users to see first. And they can
we want users to see first. And they can display key information like job count,
display key information like job count, median salary, and even that previous
median salary, and even that previous five-star ranking that we did
five-star ranking that we did previously. Can show it here. So, let's
previously. Can show it here. So, let's get into building some cards.
So, in our canvas, I've created this new page. I'm going to go ahead and call it
page. I'm going to go ahead and call it something like cards, real original. And
something like cards, real original. And I'm going to insert our first one that
I'm going to insert our first one that we're going to go over, and that's card.
we're going to go over, and that's card. All right, with this we have a field
All right, with this we have a field attribute that we can drag into. We're
attribute that we can drag into. We're going to start simple by just showing
going to start simple by just showing the median yearly salary. So I'm going
the median yearly salary. So I'm going to drag salary year average in there. It
to drag salary year average in there. It does some aggregation. We're going to
does some aggregation. We're going to change this to median. All right. So
change this to median. All right. So this shows the value and then underneath
this shows the value and then underneath it says median year average. I'm
it says median year average. I'm actually going to change that to median
actually going to change that to median yearly salary USD. Now we can do some
yearly salary USD. Now we can do some formatting to clean this up.
formatting to clean this up. Specifically going under format value. I
Specifically going under format value. I can go into the callout value. I can
can go into the callout value. I can make that a little bit bigger if I
make that a little bit bigger if I wanted to. I can then also go into the
wanted to. I can then also go into the category label. make this one a little
category label. make this one a little bit bigger, maybe even bold it. But
bit bigger, maybe even bold it. But overall, that's about it. All the
overall, that's about it. All the specializations we can do with that card
specializations we can do with that card visual. But I actually have another
visual. But I actually have another visual that I would recommend instead of
visual that I would recommend instead of this one.
this one. And that brings us to our next visual,
And that brings us to our next visual, which instead of this card right here,
which instead of this card right here, we're going to use this card parenthesis
we're going to use this card parenthesis new. So this one actually has multiple
new. So this one actually has multiple different fields within it. We're just
different fields within it. We're just going to focus on the data field right
going to focus on the data field right now to compare what these two look like.
now to compare what these two look like. I'm going to drag in that salary year
I'm going to drag in that salary year average into there. Make it into the
average into there. Make it into the median value and then call it median
median value and then call it median yearly salary. Now, I prefer this
yearly salary. Now, I prefer this visual, this card new over the other one
visual, this card new over the other one because the title is up at the top and
because the title is up at the top and in my mind you're it's more intuitive to
in my mind you're it's more intuitive to the end user for them to actually view.
the end user for them to actually view. Now, I don't like that it centers it to
Now, I don't like that it centers it to the left. So, under format your visual
the left. So, under format your visual for this card, I can go into callout
for this card, I can go into callout value, go down to the values, I can
value, go down to the values, I can change this to center, and then I can
change this to center, and then I can even bump up the size if I wanted to to
even bump up the size if I wanted to to match 50. And then for the label itself,
match 50. And then for the label itself, I could bump this one up too. Make it
I could bump this one up too. Make it bold to make it a little bit more
bold to make it a little bit more readable. Now, I'm also not necessarily
readable. Now, I'm also not necessarily a fan of how it's drawn a border around
a fan of how it's drawn a border around this one and not this one. If I wanted
this one and not this one. If I wanted to, once again, if I need to search for
to, once again, if I need to search for something, I go into search, type in
something, I go into search, type in borders, make it a lot easier. or let's
borders, make it a lot easier. or let's just try border. Scroll on down. I can
just try border. Scroll on down. I can say here for header or sorry for the
say here for header or sorry for the card section I can turn off that border.
card section I can turn off that border. Now you be the judge for it. Which one
Now you be the judge for it. Which one do you prefer of these? Now building
do you prefer of these? Now building single cards is not the only capability
single cards is not the only capability of this. We can actually do multiple
of this. We can actually do multiple cards with this card new. I'm actually
cards with this card new. I'm actually going to slide this up here and we're
going to slide this up here and we're going to insert in a new card visual
going to insert in a new card visual underneath it to demonstrate this. So
underneath it to demonstrate this. So inside the data field of this the field
inside the data field of this the field well I can drag in something like salary
well I can drag in something like salary year average put in like we did median
year average put in like we did median but we can stick multiple values in
but we can stick multiple values in here. So I can also stick that of hourly
here. So I can also stick that of hourly in here aggregating by median and it's
in here aggregating by median and it's in one single card. I'm not a fan how
in one single card. I'm not a fan how it's centering it. So I'm going to go in
it's centering it. So I'm going to go in here into call out values and change it
here into call out values and change it to center. Okay. But that's not the only
to center. Okay. But that's not the only thing with this. Right. We got this data
thing with this. Right. We got this data field. I also can do categories with
field. I also can do categories with this. Specifically, I can drag job title
this. Specifically, I can drag job title short into here. And it's showing me for
short into here. And it's showing me for each of the different job titles. I can
each of the different job titles. I can scroll down to see more. I can see this
scroll down to see more. I can see this all. So, if I wanted to, I could sorry,
all. So, if I wanted to, I could sorry, I could put this over here. Expand this
I could put this over here. Expand this all the way up. Oh, only three are
all the way up. Oh, only three are showing. Why is that? If I want to
showing. Why is that? If I want to adjust this, I would go into format
adjust this, I would go into format visual visual under layouts, I find that
visual visual under layouts, I find that under in the layout, if I change this to
under in the layout, if I change this to something like grid, I can get a little
something like grid, I can get a little bit more. We're adjusting this to a max
bit more. We're adjusting this to a max R of two and column shown of one, but
R of two and column shown of one, but still kind of unreadable. It's too much
still kind of unreadable. It's too much data. We're just actually going to go
data. We're just actually going to go back to what it was previously. And I'm
back to what it was previously. And I'm going to go stick in that corner down
going to go stick in that corner down there. Anyway, this is my preferred
there. Anyway, this is my preferred visual out of every visual we're going
visual out of every visual we're going to show here today. Mainly because of
to show here today. Mainly because of what we demonstrated above to get that
what we demonstrated above to get that title above what the callout value is.
Next up is this gauge card and it can be used in certain situations specifically
used in certain situations specifically for us for this yearly salary. We can
for us for this yearly salary. We can use it in a manner to show what is the
use it in a manner to show what is the median salary but also what's the
median salary but also what's the minimum what's the maximum that 920,000
minimum what's the maximum that 920,000 and then what is this average or target
and then what is this average or target value. So inside of our canvas I'm going
value. So inside of our canvas I'm going to insert this gauge card. I'm going to
to insert this gauge card. I'm going to put in this top quadrant right here.
put in this top quadrant right here. Now, for the value itself, I'm going to
Now, for the value itself, I'm going to go ahead and expand this into focus
go ahead and expand this into focus mode. For the value itself, we're going
mode. For the value itself, we're going to put in that salary year average. And
to put in that salary year average. And remember, we want that to be a median
remember, we want that to be a median value. Automatically with this gauge
value. Automatically with this gauge card, whenever they put in this median
card, whenever they put in this median value, it automatically puts the minimum
value, it automatically puts the minimum or the the minimum as zero and the
or the the minimum as zero and the maximum as double that. So, where the
maximum as double that. So, where the gauge goes in the middle. Anyway, we can
gauge goes in the middle. Anyway, we can set the minimum and maximum values by
set the minimum and maximum values by dragging these over into here,
dragging these over into here, specifying, hey, we want the minimum for
specifying, hey, we want the minimum for this. And now we can see, hey, the
this. And now we can see, hey, the minimum is 15,000. Similarly, I can drag
minimum is 15,000. Similarly, I can drag this into the maximum value. And we can
this into the maximum value. And we can make that well the maximum. And then
make that well the maximum. And then they also have this target value. We
they also have this target value. We don't really have a target per se, but
don't really have a target per se, but you could put in our case, I'm going to
you could put in our case, I'm going to drag the salary average in there. And
drag the salary average in there. And we'll just put in the average in there.
we'll just put in the average in there. Now, this does have a tool tip come up.
Now, this does have a tool tip come up. So, it's behoo of you to go through and
So, it's behoo of you to go through and actually put in what is the actual names
actually put in what is the actual names for these. And so, we can see that the
for these. And so, we can see that the median salary is 113,000. Average salary
median salary is 113,000. Average salary is 120,000. Let's go back to our report,
is 120,000. Let's go back to our report, see how I've viewed from this. Not too
see how I've viewed from this. Not too bad. Like usual, let's actually update
bad. Like usual, let's actually update that title. So, we're going to change
that title. So, we're going to change that to median yearly salary. I'm also
that to median yearly salary. I'm also going to bump the font up and center it.
going to bump the font up and center it. We can also change the font of other
We can also change the font of other things like these data labels which are
things like these data labels which are the min and max values. I could bump it
the min and max values. I could bump it up to something like 20. For that
up to something like 20. For that average value, I could go to that target
average value, I could go to that target label, make this also 20. Also take off
label, make this also 20. Also take off the decimal places off that. I don't
the decimal places off that. I don't want that on there. And then finally for
want that on there. And then finally for the callout value itself, I can adjust
the callout value itself, I can adjust things like the font if I wanted to make
things like the font if I wanted to make it bold. And that's about it. That will
it bold. And that's about it. That will move with it. Fortunately, you can't, or
move with it. Fortunately, you can't, or at least underneath here, I can't
at least underneath here, I can't control the size of this callout value.
Next up is a multi-row card. And like the name implies, it has multiple rows.
the name implies, it has multiple rows. To make things easier on ourselves, I'm
To make things easier on ourselves, I'm going to take that card new, do a
going to take that card new, do a control crl +v, and then with this
control crl +v, and then with this selected, I'm going to then change this
selected, I'm going to then change this into this one of this multi-row card.
into this one of this multi-row card. All right. In our case where we had
All right. In our case where we had those 10 different job titles and using
those 10 different job titles and using in that card new I think this multi-ro
in that card new I think this multi-ro card going into this focus mode it's a
card going into this focus mode it's a lot more readable and a lot more
lot more readable and a lot more userfriendly and intuitive. I could even
userfriendly and intuitive. I could even drag in if I wanted to something like
drag in if I wanted to something like job title short and we can get an
job title short and we can get an aggregation of it specifically of count.
aggregation of it specifically of count. As usual you want to go through and
As usual you want to go through and clean up all the field names to make it
clean up all the field names to make it a lot more presentable. But overall
a lot more presentable. But overall pretty happy with this.
The last card to talk about is a KPI card. There's a lot going on here, but
card. There's a lot going on here, but the main purpose of this is to show a
the main purpose of this is to show a callout value, if you will, and then
callout value, if you will, and then from there, some sort of trend that's
from there, some sort of trend that's going on in the background. If you're at
going on in the background. If you're at or above your goal for whatever you're
or above your goal for whatever you're doing, whether it's sales or returns or
doing, whether it's sales or returns or whatever it may be, it's going to be
whatever it may be, it's going to be green. If it's below, it's going to be
green. If it's below, it's going to be red. Hopefully, it goes without saying.
red. Hopefully, it goes without saying. You could change the colors if you want
You could change the colors if you want to. Anyway, let's build this bad boy.
to. Anyway, let's build this bad boy. I'm gonna take this visual right here.
I'm gonna take this visual right here. Here, I'm going to copy it and then
Here, I'm going to copy it and then paste it. We're running out of room on
paste it. We're running out of room on here, so I'm going to just slide some
here, so I'm going to just slide some stuff around. With this new card
stuff around. With this new card selected and down at the bottom, I'm
selected and down at the bottom, I'm going to now change this into a KPI
going to now change this into a KPI card. And it's not going to show
card. And it's not going to show anything. It says, hey, fields for both
anything. It says, hey, fields for both value and trend axis are needed. So, for
value and trend axis are needed. So, for the trend axis, what we want to look at
the trend axis, what we want to look at over time, I'm going to say we want to
over time, I'm going to say we want to look at that monthly job posted date.
look at that monthly job posted date. Okay, taking this into focus mode to
Okay, taking this into focus mode to look a little bit more into it. So
look a little bit more into it. So what's going in the background is it's
what's going in the background is it's showing how that median salary is
showing how that median salary is changing over time. Right now we don't
changing over time. Right now we don't have a target. Unfortunately I don't
have a target. Unfortunately I don't have any data to if you will show a
have any data to if you will show a target for this. Like there's not
target for this. Like there's not another column for target salary based
another column for target salary based in that time frame or something like
in that time frame or something like that. So all I can do is just throw in
that. So all I can do is just throw in something like the yearly salary into
something like the yearly salary into there. Right now, it's doing an
there. Right now, it's doing an aggregation based on the sum, which
aggregation based on the sum, which apparently that's less than what the
apparently that's less than what the median is. I don't know how that's
median is. I don't know how that's possible, but if I set it to the median
possible, but if I set it to the median itself to basically set it equal to
itself to basically set it equal to itself, it's 0%, it equals itself. It
itself, it's 0%, it equals itself. It maintains green. Once again, this is for
maintains green. Once again, this is for data that maybe has you have your some
data that maybe has you have your some sales data and then some target sales
sales data and then some target sales data. And then you could combine the two
data. And then you could combine the two to combine whether you want to have this
to combine whether you want to have this green or red value show for these
green or red value show for these values. All right, it's your turn now to
values. All right, it's your turn now to go through with those practice problems
go through with those practice problems to get more in depth and familiar with
to get more in depth and familiar with how to use these different cards. In the
how to use these different cards. In the next lesson, we're going to be jumping
next lesson, we're going to be jumping into slicers and we're almost well, two
into slicers and we're almost well, two more lessons left and we'll be done with
more lessons left and we'll be done with this chapter. With that, I'll see you
this chapter. With that, I'll see you there.
All right, two more lessons and we're going to be getting into our project. In
going to be getting into our project. In this lesson, we're going to be covering
this lesson, we're going to be covering slicers, and it's a great way to prompt
slicers, and it's a great way to prompt your users to interact with their data
your users to interact with their data in order to make selections and dive in
in order to make selections and dive in deeper to find insights. All right, here
deeper to find insights. All right, here I am inside of our final solutions file.
I am inside of our final solutions file. In it, we're going to be going through
In it, we're going to be going through all the different slicers. In no way do
all the different slicers. In no way do I ever recommend you actually make a
I ever recommend you actually make a report with this many slicers inside of
report with this many slicers inside of a report, but this is mainly for demo so
a report, but this is mainly for demo so we can see all the different types that
we can see all the different types that are available. We'll have a little bonus
are available. We'll have a little bonus section at the end that whenever we
section at the end that whenever we filter down to whatever data we want,
filter down to whatever data we want, we're going to add this button to where
we're going to add this button to where if we want to clear all slicers, we can
if we want to clear all slicers, we can just click that and it'll clear it. So,
just click that and it'll clear it. So, little bonus.
So, let's get into the three major types of slicers. I'm going to create a new
of slicers. I'm going to create a new page right here and call it slicers.
page right here and call it slicers. Inside of our canvas, I'm going to go
Inside of our canvas, I'm going to go ahead and insert in a slicer. Let's go
ahead and insert in a slicer. Let's go into focus mode. And for this, we're
into focus mode. And for this, we're going to keep it simple. We're going to
going to keep it simple. We're going to just go into the job title short
just go into the job title short portion. All right. So, this is our
portion. All right. So, this is our slicer. Right now, we can select
slicer. Right now, we can select basically one uh value at a time. Now
basically one uh value at a time. Now the three major types of slicers going
the three major types of slicers going under format your visual under slicer
under format your visual under slicer settings are controlled in here right
settings are controlled in here right now. The style they have vertical list
now. The style they have vertical list which is what we're seeing tile. So I
which is what we're seeing tile. So I could select different options like this
could select different options like this and then the other option which I uh
and then the other option which I uh also really like are is the dropdown to
also really like are is the dropdown to where the user has to go in select the
where the user has to go in select the dropdown. They do may have to scroll,
dropdown. They do may have to scroll, but they can select what they want
but they can select what they want inside of here and then still see that
inside of here and then still see that it's selected. Now, let's actually see
it's selected. Now, let's actually see this interact with the report. I'm going
this interact with the report. I'm going to go to our column and bar chart
to go to our column and bar chart example that we put together or the page
example that we put together or the page we put together. I'm going to copy this
we put together. I'm going to copy this report and then paste it right here
report and then paste it right here underneath here. And then you can see as
underneath here. And then you can see as I paste it in here, it already filter
I paste it in here, it already filter down to what I want, which actually
down to what I want, which actually brings up our next point. What happens
brings up our next point. What happens if we want to quickly clear it? like
if we want to quickly clear it? like yeah I can come in here and uncheck that
yeah I can come in here and uncheck that but that's a little little burdensome.
but that's a little little burdensome. Um so instead if we have something
Um so instead if we have something selected like data analyst in this case
selected like data analyst in this case if you notice whenever I'm on top of the
if you notice whenever I'm on top of the slicer I can come up here to the top and
slicer I can come up here to the top and select clear selection and then it
select clear selection and then it updates with the selection clear. Now
updates with the selection clear. Now this always in is isn't intuitive to end
this always in is isn't intuitive to end users. So at the end of this lesson
users. So at the end of this lesson we're going over how we can create that
we're going over how we can create that button to clear all slicers if we want
button to clear all slicers if we want to. I'm going to do some formatting
to. I'm going to do some formatting changes just to make it a little bit
changes just to make it a little bit more visual as we go through some of
more visual as we go through some of these demos. I'm make this graph all the
these demos. I'm make this graph all the way big and make this take up this. I'm
way big and make this take up this. I'm also going to change the font size. You
also going to change the font size. You don't need to do this unless you want
don't need to do this unless you want to, but I'm going to make it a lot
to, but I'm going to make it a lot bigger so we can actually see it. All
bigger so we can actually see it. All right, let's go over some functionality
right, let's go over some functionality more on this. I'm going to transfer this
more on this. I'm going to transfer this back into a vertical list. Okay, the
back into a vertical list. Okay, the first thing is this. What happens if I
first thing is this. What happens if I want like in this case there's only 10
want like in this case there's only 10 values, but imagine if there's a 100
values, but imagine if there's a 100 values and I need to search through it.
values and I need to search through it. How am I going to be able to do that?
How am I going to be able to do that? Well, I can click the ellipses up here
Well, I can click the ellipses up here and select search. And this now enables
and select search. And this now enables search within here. So, I could search
search within here. So, I could search for something like, hey, which ones
for something like, hey, which ones contain the word data? And all of them
contain the word data? And all of them pop up. The next thing is what if I want
pop up. The next thing is what if I want to select multiple values? So, in this
to select multiple values? So, in this case, I have data analyst, b business
case, I have data analyst, b business anal like I can't select multiple
anal like I can't select multiple values. What am I supposed to do here?
values. What am I supposed to do here? Well, if we go under format your visual
Well, if we go under format your visual visuals and then slicer settings under
visuals and then slicer settings under selection, we can see that by default
selection, we can see that by default multi- select with control or command is
multi- select with control or command is enabled right now. So if the user wants
enabled right now. So if the user wants to input multiple values in this, they
to input multiple values in this, they have to hold control and then select all
have to hold control and then select all the multiple different values. Kind of
the multiple different values. Kind of annoying if you ask me. Now let's say
annoying if you ask me. Now let's say you only want them to select one value
you only want them to select one value at a time. Well, you can turn this
at a time. Well, you can turn this single select on and then it turns into
single select on and then it turns into radio buttons which prompts them that
radio buttons which prompts them that hey, you can only do one value at a
hey, you can only do one value at a time. In this case with job titles,
time. In this case with job titles, that's not necessarily applicable. So,
that's not necessarily applicable. So, I'm going to turn that off. And then the
I'm going to turn that off. And then the other one I am going to enable that's
other one I am going to enable that's not enabled by default that you should
not enabled by default that you should turn on typically is show select all.
turn on typically is show select all. And this is a fast way for them besides
And this is a fast way for them besides using that clear slicer to just hey,
using that clear slicer to just hey, select all to get back to where they
select all to get back to where they need to get to. For the time being, I'm
need to get to. For the time being, I'm going to switch this up and we're going
going to switch this up and we're going to just change this into tile. And it
to just change this into tile. And it works in the same way. I can select
works in the same way. I can select multiple values by holding control and
multiple values by holding control and then going through and clicking on the
then going through and clicking on the buttons.
Now, for categories, these are the three major types, vertical list, tile, and
major types, vertical list, tile, and drop down. But there's actually other
drop down. But there's actually other types of slicers. Let's find out how we
types of slicers. Let's find out how we can make those. So, I'm going to come in
can make those. So, I'm going to come in and create a new slicer. And I could
and create a new slicer. And I could drag in a number column or in this case
drag in a number column or in this case I'm going to drag in a date column. Now
I'm going to drag in a date column. Now for this one it's using what we call a
for this one it's using what we call a between slicer. I know this I can go
between slicer. I know this I can go into format your visual slicer settings.
into format your visual slicer settings. And now when I do this drop down there's
And now when I do this drop down there's a lot more different options in here.
a lot more different options in here. You can do between um between meaning I
You can do between um between meaning I can slide this and move it anywhere
can slide this and move it anywhere between. We can see that the data did
between. We can see that the data did update during that time. I could do
update during that time. I could do before where only on one side it's
before where only on one side it's allowed me to move. after on the other
allowed me to move. after on the other side allowed me to move drop down as we
side allowed me to move drop down as we saw before not no change here for that
saw before not no change here for that they do have this one on relative date
they do have this one on relative date or relative time this one I can't really
or relative time this one I can't really even see this this allows you to filter
even see this this allows you to filter based on something like oh the last one
based on something like oh the last one if we wanted to last one years and then
if we wanted to last one years and then we can't see anything actually let's go
we can't see anything actually let's go back to the report oh it's not working
back to the report oh it's not working this is actually known issue let me show
this is actually known issue let me show you what I mean I'm going to actually
you what I mean I'm going to actually switch this back to between. I'm going
switch this back to between. I'm going to go and clear the selection so that
to go and clear the selection so that way this and I actually had to drag this
way this and I actually had to drag this end date down to get it to work after
end date down to get it to work after switching it to between. Anyway, this is
switching it to between. Anyway, this is a known issue with PowerBI. As you see,
a known issue with PowerBI. As you see, whenever I drag that start date back and
whenever I drag that start date back and forward, it's causing the filters or
forward, it's causing the filters or causing the other visuals to end up
causing the other visuals to end up breaking. And so, what I have to do is I
breaking. And so, what I have to do is I have to basically clear selection and
have to basically clear selection and then it gets back to working. Anyway,
then it gets back to working. Anyway, this is a bug. Somebody on Reddit
this is a bug. Somebody on Reddit reported this a month ago, filming this
reported this a month ago, filming this in May of 2025. So maybe by the time
in May of 2025. So maybe by the time you're filming this or sorry, you're
you're filming this or sorry, you're actually going through this, you won't
actually going through this, you won't have this error coming up. But just know
have this error coming up. But just know that Microsoft is aware of this issue
that Microsoft is aware of this issue and they're trying to troubleshoot to
and they're trying to troubleshoot to fix this. So anytime you enter this
fix this. So anytime you enter this error error by just like filtering by
error error by just like filtering by start date, you can just clear the
start date, you can just clear the selection. Right now, I'm going to
selection. Right now, I'm going to recommend we don't use any between
recommend we don't use any between filters because of this. Specifically
filters because of this. Specifically for any dashboards that we're trying to
for any dashboards that we're trying to build. Hey, we can also do one other
build. Hey, we can also do one other thing with this specifically. We're not
thing with this specifically. We're not limited to just dates. If I wanted to, I
limited to just dates. If I wanted to, I could take something like the salary
could take something like the salary data and stick it into the field. I'm
data and stick it into the field. I'm going to get rid of this and then change
going to get rid of this and then change this visual or the slicer setting back
this visual or the slicer setting back to between. But now I could adjust what
to between. But now I could adjust what salary range I want to look at for this.
salary range I want to look at for this. Now, for all of these slicers, I do
Now, for all of these slicers, I do recommend updating the title to make it
recommend updating the title to make it more intuitive of what's going on here.
more intuitive of what's going on here. You can adjust it underneath the slicer
You can adjust it underneath the slicer header, but I'm going to recommend just
header, but I'm going to recommend just going into the field and changing it to
going into the field and changing it to an intuitive title like this one's of
an intuitive title like this one's of filter salary range. Our top title one
filter salary range. Our top title one now is select job title. And then update
now is select job title. And then update this one to something like filter
this one to something like filter posting date.
posting date. So, what happens if we want to use
So, what happens if we want to use slicers on multiple different pages?
slicers on multiple different pages? Well, we do have an an option to sync
Well, we do have an an option to sync slicer. So, in this case, I'm going to
slicer. So, in this case, I'm going to take this tile slicer that we have right
take this tile slicer that we have right here and copy it. And then we're going
here and copy it. And then we're going to go to the column and bar page. I'm
to go to the column and bar page. I'm going to paste this bad boy into here.
going to paste this bad boy into here. And it's going to say this. Hey, do you
And it's going to say this. Hey, do you want to sync slicers or sync visuals?
want to sync slicers or sync visuals? One or more of these copy visuals can
One or more of these copy visuals can stay in sync with the visual is copied
stay in sync with the visual is copied from. Do you want to keep them in sync?
from. Do you want to keep them in sync? In most all cases, I do want to do this.
In most all cases, I do want to do this. Now, if you remember back to our column
Now, if you remember back to our column and bar lesson, we did a filter on this
and bar lesson, we did a filter on this page for job title short for all job
page for job title short for all job titles that contain the word data. So,
titles that contain the word data. So, in this case, there's only six values
in this case, there's only six values here. Seven if you include se select
here. Seven if you include se select all. Anyway, if I make a selection like
all. Anyway, if I make a selection like in this case, I'm going hold control and
in this case, I'm going hold control and do data analyst, data engineer, and data
do data analyst, data engineer, and data scientist. All three selected. And then
scientist. All three selected. And then when I go back to the slicers page,
when I go back to the slicers page, these are also selected here. Now, what
these are also selected here. Now, what if I want to unsync it or customize the
if I want to unsync it or customize the syncing behavior more? Well, in the
syncing behavior more? Well, in the ribbon, if we navigate to the view tab
ribbon, if we navigate to the view tab and we go to sync slicers, I'm going to
and we go to sync slicers, I'm going to close out of data. And also in
close out of data. And also in visualizations, we have a sync slicers
visualizations, we have a sync slicers popup. I'm going to select the slicer
popup. I'm going to select the slicer that I want to investigate further. And
that I want to investigate further. And it provides a list of all the different
it provides a list of all the different pages we have. So column and bar all the
pages we have. So column and bar all the way to slicers. This first column right
way to slicers. This first column right here indicates whether the slicer is
here indicates whether the slicer is synced between the other page. And then
synced between the other page. And then this other one indicates whether it's
this other one indicates whether it's visible or not. So on this slicer page I
visible or not. So on this slicer page I could make this unvisible or invisible
could make this unvisible or invisible and uh take it away. Typically I would
and uh take it away. Typically I would just delete it. Anyway, you could we
just delete it. Anyway, you could we could also unsync it. So if I wanted to
could also unsync it. So if I wanted to unsync these slicers I could unsink
unsync these slicers I could unsink unsync it here. And now on this page,
unsync it here. And now on this page, I'm going to select senior roles and
I'm going to select senior roles and remove these. However, when I navigate
remove these. However, when I navigate back to column and bar, the data is
back to column and bar, the data is still filtered for data engineer, data
still filtered for data engineer, data scientist, data analyst. However, it's
scientist, data analyst. However, it's filtered down and our slicer is missing.
filtered down and our slicer is missing. This is actually sort of weird behavior,
This is actually sort of weird behavior, but if we go into view and I go into
but if we go into view and I go into selection to show this up, we can see
selection to show this up, we can see all the different visuals in here,
all the different visuals in here, right? You know, you can do the hide if
right? You know, you can do the hide if you want to or not. The slicer became
you want to or not. The slicer became hidden because we basically unhid it.
hidden because we basically unhid it. Anyway, we have those three values right
Anyway, we have those three values right here. I'm going to go ahead. I don't
here. I'm going to go ahead. I don't want this slicer on this page anyway, so
want this slicer on this page anyway, so we're going to go ahead and just delete
we're going to go ahead and just delete it anyway. But now we understand how we
it anyway. But now we understand how we can sync slicers between different
can sync slicers between different pages. In almost all situations, like I
pages. In almost all situations, like I said, I'm going to sync slice between
said, I'm going to sync slice between pages to make it that much easier for
pages to make it that much easier for the enduser to navigate between pages
the enduser to navigate between pages and have their current selections
and have their current selections maintained as they go throughout.
Last thing to talk about is the clear all slicers button. Like I mentioned
all slicers button. Like I mentioned previously, this isn't necessarily of
previously, this isn't necessarily of clear selections of the top of the drop
clear selections of the top of the drop down. It's not necessarily super
down. It's not necessarily super intuitive for users to click to clear
intuitive for users to click to clear their slicers. So, open the ribbon under
their slicers. So, open the ribbon under insert. I'm going to go to buttons and
insert. I'm going to go to buttons and we're going to insert a button of clear
we're going to insert a button of clear all slicers. Let's make room for this up
all slicers. Let's make room for this up at the top. Going to drag that right
at the top. Going to drag that right into the center right here. So now, so
into the center right here. So now, so let's say I go through and make some
let's say I go through and make some different selections and filter also for
different selections and filter also for a certain date. Whenever I want to clear
a certain date. Whenever I want to clear this, I can just come up to clear all
this, I can just come up to clear all slicers, press control, and click it. If
slicers, press control, and click it. If I want to dress this button up a little
I want to dress this button up a little bit and go under the format buttons
bit and go under the format buttons under style, make the font a little bit
under style, make the font a little bit bigger, make it bold, go down to fill,
bigger, make it bold, go down to fill, turn it on, change it to this blue
turn it on, change it to this blue color, and then maybe put something like
color, and then maybe put something like a shadow underneath it to make it stand
a shadow underneath it to make it stand out a little bit more. Also, not really
out a little bit more. Also, not really a fan of rectangles. So, underneath
a fan of rectangles. So, underneath shape in here, I can come under this and
shape in here, I can come under this and I can just change this to round
I can just change this to round rectangle. All right, good enough. Now,
rectangle. All right, good enough. Now, there's one other button I want to call
there's one other button I want to call your attention to that you can add to
your attention to that you can add to this. I'm going to go under the optimize
this. I'm going to go under the optimize tab on the ribbon, and it's an apply all
tab on the ribbon, and it's an apply all slicers button. And I'm going to drag
slicers button. And I'm going to drag that over here for the time being and
that over here for the time being and drag this over. Let's first demo it, and
drag this over. Let's first demo it, and then I'll explain it. I'm going to make
then I'll explain it. I'm going to make multiple different selections. So, data
multiple different selections. So, data analyst, also data engineers, and then
analyst, also data engineers, and then data scientist. You notice the button
data scientist. You notice the button went from that light gray to a dark
went from that light gray to a dark gray. I'll also change the date also
gray. I'll also change the date also during this which I didn't call out none
during this which I didn't call out none of the data updated. So now I can click
of the data updated. So now I can click controllclick this and now the data will
controllclick this and now the data will update. Now why would you want to do
update. Now why would you want to do this? So I cleared all slicers. If I go
this? So I cleared all slicers. If I go through and just actually select all the
through and just actually select all the items as it's filtering. Actually I have
items as it's filtering. Actually I have to get rid of this button to actually
to get rid of this button to actually demo that. I'm going to go ahead and
demo that. I'm going to go ahead and remove it. Yeah, this will change the uh
remove it. Yeah, this will change the uh slicer behavior, but mainly I want to
slicer behavior, but mainly I want to just demonstrate whenever I'm clicking
just demonstrate whenever I'm clicking this, the data is updating pretty dang
this, the data is updating pretty dang quickly. So something like that of
quickly. So something like that of underneath the optimize tab of this
underneath the optimize tab of this apply all slicers button in this case
apply all slicers button in this case based on how small the data set is, not
based on how small the data set is, not really useful and probably going to
really useful and probably going to cause more confusion for the end user.
cause more confusion for the end user. This type of button would be used in
This type of button would be used in cases where there's a very large data
cases where there's a very large data set and it's taking a long time for the
set and it's taking a long time for the data to refresh. And so instead, I'd
data to refresh. And so instead, I'd allow them to select all what they
allow them to select all what they wanted to do and then apply the update
wanted to do and then apply the update to all the visuals. So if you have this
to all the visuals. So if you have this on there of this apply all slicers, go
on there of this apply all slicers, go ahead and remove it. We're not going to
ahead and remove it. We're not going to use it and going to go ahead and clear
use it and going to go ahead and clear all slicers as well. All right. So you
all slicers as well. All right. So you have some practice problems and now go
have some practice problems and now go through and get more familiar with using
through and get more familiar with using all these different slicers and also
all these different slicers and also some practice with buttons. In the next
some practice with buttons. In the next lesson, which conveniently we just had a
lesson, which conveniently we just had a intro to buttons, we go further in
intro to buttons, we go further in detail on buttons and also bookmarks. So
detail on buttons and also bookmarks. So with that, I'll see you there.
Welcome to this last lesson this chapter on buttons and bookmarks. And I may be a
on buttons and bookmarks. And I may be a little biased, but this is by far my
little biased, but this is by far my favorite section because we're going to
favorite section because we're going to have a lot more fun with PowerBI. Now,
have a lot more fun with PowerBI. Now, in our solutions notebook, let me show
in our solutions notebook, let me show you what I mean. So, in the first half,
you what I mean. So, in the first half, we're going to be covering buttons.
we're going to be covering buttons. Buttons aren't really that difficult,
Buttons aren't really that difficult, and you've made some already. In this
and you've made some already. In this case, I want to go to a certain lesson
case, I want to go to a certain lesson in here. I can navigate with the witch
in here. I can navigate with the witch chart, and it navigates me to that page,
chart, and it navigates me to that page, and then I can navigate back. All this
and then I can navigate back. All this was configured with buttons. We're going
was configured with buttons. We're going to build something similar to this for
to build something similar to this for the first half of this lesson. Now, for
the first half of this lesson. Now, for the second half, we're going to move on
the second half, we're going to move on to a more complex topic of bookmarks.
to a more complex topic of bookmarks. Anyway, let me show you what bookmarks
Anyway, let me show you what bookmarks can do. Here we are on our page of
can do. Here we are on our page of column and bar charts. And I have this
column and bar charts. And I have this button up at the top for a bookmark. And
button up at the top for a bookmark. And whenever I click controllclick onto the
whenever I click controllclick onto the button, I have appearing on top of our
button, I have appearing on top of our visuals a slicer that allows us to
visuals a slicer that allows us to navigate down to whatever data I want.
navigate down to whatever data I want. So I'll make a few selections. And then
So I'll make a few selections. And then once I'm done making those selections, I
once I'm done making those selections, I can go ahead and click this button to
can go ahead and click this button to close it off. And it's filtered down.
close it off. And it's filtered down. Anyway, revealing the magic behind the
Anyway, revealing the magic behind the scenes. Going to the view tab under
scenes. Going to the view tab under bookmarks. I can see that this is
bookmarks. I can see that this is controlled via bookmarks, specifically
controlled via bookmarks, specifically this bookmark here. and this bookmark
this bookmark here. and this bookmark here, which we're going to be building
here, which we're going to be building during this lesson. And these bookmarks
during this lesson. And these bookmarks are just placed inside of the action for
are just placed inside of the action for the button themselves. Okay. Anyway, I'm
the button themselves. Okay. Anyway, I'm getting ahead of myself. Let's actually
getting ahead of myself. Let's actually get into buttons.
get into buttons. Like I mentioned, we're going to be
Like I mentioned, we're going to be building a page like this. So, inside of
building a page like this. So, inside of our PowerBI report that we're on, we
our PowerBI report that we're on, we need to first create a new page for this
need to first create a new page for this homepage. I'm going to go ahead and name
homepage. I'm going to go ahead and name it home. And then I'm going to
it home. And then I'm going to rightclick it. Instead of trying to drag
rightclick it. Instead of trying to drag it over, I'm going go to move to and I'm
it over, I'm going go to move to and I'm going to move to front. Inside of this
going to move to front. Inside of this blank pan canvas, I'm going to insert a
blank pan canvas, I'm going to insert a title. We can do this by going to the
title. We can do this by going to the insert tab and just inserting a text
insert tab and just inserting a text box. And then in my case, I'm just going
box. And then in my case, I'm just going to format say chapter 2 visualizations
to format say chapter 2 visualizations real original. All right, let's build
real original. All right, let's build those buttons for the different pages.
those buttons for the different pages. This one's actually really simple.
This one's actually really simple. Underneath buttons, I'm going to go to
Underneath buttons, I'm going to go to navigator and then page navigator. These
navigator and then page navigator. These buttons then pop up. I'm going to move
buttons then pop up. I'm going to move them and recenter it. We're going to
them and recenter it. We're going to format it here in a little bit, but just
format it here in a little bit, but just want to demonstrate how it is working
want to demonstrate how it is working right now. Right, home is we're on home,
right now. Right, home is we're on home, so it's automatically black. And then
so it's automatically black. And then column bar. If I want to go to that, I'm
column bar. If I want to go to that, I'm going to click control. And then I'm
going to click control. And then I'm going to be able to navigate to it. So,
going to be able to navigate to it. So, let's format it by ensuring we're
let's format it by ensuring we're selected on it. Go into the format
selected on it. Go into the format navigator and under shape. You know, I
navigator and under shape. You know, I don't like rectangles. I like rounded
don't like rectangles. I like rounded rectangles. Next, I'm going to go into
rectangles. Next, I'm going to go into the grid layout to adjust how it's done.
the grid layout to adjust how it's done. And we're going to change this from
And we're going to change this from horizontal to grid. And from this we can
horizontal to grid. And from this we can specify how many rows and how many
specify how many rows and how many columns. For this we're going to say
columns. For this we're going to say three rows and three columns. Now
three rows and three columns. Now navigating underneath style I'm going to
navigating underneath style I'm going to change the font size to a little bit
change the font size to a little bit bigger. Make it bold. And if you notice
bigger. Make it bold. And if you notice it only changed these buttons. It didn't
it only changed these buttons. It didn't change our home one. And that's because
change our home one. And that's because that's the selected one. So we can also
that's the selected one. So we can also change this one to 20. Anyway, going
change this one to 20. Anyway, going back to those that are default. We can
back to those that are default. We can then go into under fill. And you know I
then go into under fill. And you know I love me some light blue. So, we'll stick
love me some light blue. So, we'll stick with that. And then we'll also enable
with that. And then we'll also enable the shadow to make it look a little more
the shadow to make it look a little more poppy to entice people to press the
poppy to entice people to press the buttons. All right, this is good enough.
buttons. All right, this is good enough. Now, as you remember, if we clicked on
Now, as you remember, if we clicked on something like press control and go to
something like press control and go to column bar. Yeah, we're on column bar,
column bar. Yeah, we're on column bar, but how the heck do we get back to the
but how the heck do we get back to the homepage? Well, we can add a button for
homepage? Well, we can add a button for this. Now, inside of the projects folder
this. Now, inside of the projects folder under resources and then under images,
under resources and then under images, we actually have an image in there of a
we actually have an image in there of a home icon emoji. We're going to use this
home icon emoji. We're going to use this for our button. So, underneath the
for our button. So, underneath the insert ribbon, I'm going to go to image.
insert ribbon, I'm going to go to image. We're going to navigate to that projects
We're going to navigate to that projects folder, resources, images, and then
folder, resources, images, and then select the home emoji. From there, I'm
select the home emoji. From there, I'm going to slide it up into the right hand
going to slide it up into the right hand corner to make sure it's not blocking
corner to make sure it's not blocking anything. All right. Right now, this is
anything. All right. Right now, this is just an image. There's nothing happening
just an image. There's nothing happening with it. It doesn't do any actions when
with it. It doesn't do any actions when I uh click control. We notice we have
I uh click control. We notice we have format image popup and we have action.
format image popup and we have action. And right now, it's off. So, obviously,
And right now, it's off. So, obviously, we want the action to be on. Now we can
we want the action to be on. Now we can assign different actions. We could
assign different actions. We could assign book a bookmark which we'll be
assign book a bookmark which we'll be doing later. Could assign page
doing later. Could assign page navigation which probably what we want
navigation which probably what we want to do but they also have other features
to do but they also have other features to do as well. We're going to just stick
to do as well. We're going to just stick with page navigation. For this we need
with page navigation. For this we need to specify the destination and we want
to specify the destination and we want to go home. I always want to go home. So
to go home. I always want to go home. So now with this if I go ahead and click
now with this if I go ahead and click control and then on the home button it
control and then on the home button it navigates me here and I can navigate
navigates me here and I can navigate back here. All right. Easy way. Let's go
back here. All right. Easy way. Let's go ahead and just copy this. Press Ctrl + C
ahead and just copy this. Press Ctrl + C and then I'm going to just navigate into
and then I'm going to just navigate into every single page and paste it into
every single page and paste it into there pressing commandV or controlV. All
there pressing commandV or controlV. All right, I navigated to the last page.
right, I navigated to the last page. Let's go back home. And with this,
Let's go back home. And with this, remember we have to press control plus
remember we have to press control plus the click. Some of our users that are
the click. Some of our users that are new to this may not know they need to
new to this may not know they need to press control. So, we could use what's
press control. So, we could use what's called a Q&A feature or Q&A button to
called a Q&A feature or Q&A button to prompt them to do this. So, under the
prompt them to do this. So, under the insert tab, I'm going to go to buttons
insert tab, I'm going to go to buttons and we're going to go to this one on
and we're going to go to this one on help. I'm going to stick it up in the
help. I'm going to stick it up in the right hand corner. And this is pretty
right hand corner. And this is pretty generic and understanding that users
generic and understanding that users probably need to go here if they have
probably need to go here if they have help. Now, clicking this button, I'm
help. Now, clicking this button, I'm going to go into actions itself. I want
going to go into actions itself. I want to turn on these actions. And the type
to turn on these actions. And the type of action I want to do for this is a
of action I want to do for this is a Q&A.
Q&A. Then I'm going to navigate here to under
Then I'm going to navigate here to under tool tip. the tool tip is on. And for
tool tip. the tool tip is on. And for the tool tip or the answer to the
the tool tip or the answer to the question, if you will, I'll say press
question, if you will, I'll say press control while clicking a button to
control while clicking a button to select. So now whenever I'm on this
select. So now whenever I'm on this page, if I just scroll over this, this
page, if I just scroll over this, this popup comes up says press control while
popup comes up says press control while clicking a button to select. And they
clicking a button to select. And they don't even have to actually select the
don't even have to actually select the button. Sorry, got a little bit
button. Sorry, got a little bit confused. Whenever I click control and
confused. Whenever I click control and actually click this button, it pops up
actually click this button, it pops up Q&A is not what I want. I don't want
Q&A is not what I want. I don't want Remember, we went over Q&A feature. The
Remember, we went over Q&A feature. The thing's horrendous. Instead, what we
thing's horrendous. Instead, what we want for the action for this button is
want for the action for this button is we want it to just bookmark and the
we want it to just bookmark and the bookmark to be none. So, if they were to
bookmark to be none. So, if they were to actually control-click this, nothing's
actually control-click this, nothing's actually going to happen, but they have
actually going to happen, but they have the tool tip pop up. Got a little
the tool tip pop up. Got a little confused there. And that's a great segue
confused there. And that's a great segue into our next section on bookmarks
into our next section on bookmarks because now we can see that we could set
because now we can see that we could set a bookmark as an action to a button.
So, let's get into making our first bookmark. What we need to do is go to
bookmark. What we need to do is go to view tab on the ribbon, select bookmarks
view tab on the ribbon, select bookmarks to pop it up. In it, the instructions
to pop it up. In it, the instructions are pretty simple. It says filter data
are pretty simple. It says filter data to get to the state you want to capture
to get to the state you want to capture and then click add. So, let's first just
and then click add. So, let's first just capture this state right here that we're
capture this state right here that we're in to demonstrate what's going on here.
in to demonstrate what's going on here. So, I'll click add. And nothing special
So, I'll click add. And nothing special just pops up here. Now, let's say we
just pops up here. Now, let's say we want a filtered state. Say I wanted to
want a filtered state. Say I wanted to select in this case data engineer, data
select in this case data engineer, data scientist and data analyst. By the way,
scientist and data analyst. By the way, I'm holding control for all those. And I
I'm holding control for all those. And I want to bookmark this view. Well, then I
want to bookmark this view. Well, then I would go ahead and click add. Okay,
would go ahead and click add. Okay, remember previously bookmark one is the
remember previously bookmark one is the unfiltered one. So if I were to click
unfiltered one. So if I were to click it, it's going to go to that. And if I
it, it's going to go to that. And if I go to this one, it's going to go to
go to this one, it's going to go to that. Now these names are generic. So
that. Now these names are generic. So we're going to name them real quick to
we're going to name them real quick to column and bar unfiltered and then
column and bar unfiltered and then column bar filtered. Like I said before,
column bar filtered. Like I said before, we could go in, insert a button. In this
we could go in, insert a button. In this case, I'll just insert, we'll say a
case, I'll just insert, we'll say a blank button and make it nice and big,
blank button and make it nice and big, and of course, change the fill to a
and of course, change the fill to a light blue color. We're going to end up
light blue color. We're going to end up deleting this button, so you don't need
deleting this button, so you don't need to necessarily use this. Anyway, in the
to necessarily use this. Anyway, in the action, I can turn it on. Go into here,
action, I can turn it on. Go into here, turn on bookmark, and set this bookmark
turn on bookmark, and set this bookmark to something like filtered. So now,
to something like filtered. So now, whenever I click this, pressing
whenever I click this, pressing controllclick, it's going to filter my
controllclick, it's going to filter my data. Um, but if I could click it again,
data. Um, but if I could click it again, it's not going to unfilter it. I'd have
it's not going to unfilter it. I'd have to create another button for unfiltered.
to create another button for unfiltered. Anyway, that's for demos only. We're
Anyway, that's for demos only. We're going to go ahead and just delete this
going to go ahead and just delete this button. Now, diving into this bookmark a
button. Now, diving into this bookmark a little bit further. Going to the filter,
little bit further. Going to the filter, going to the three dots associated with
going to the three dots associated with this. We can see for the popup up at the
this. We can see for the popup up at the top, they have options like update,
top, they have options like update, rename, delete. You could also g group
rename, delete. You could also g group bookmarks if you want. We're not going
bookmarks if you want. We're not going to do that. The key things down here are
to do that. The key things down here are we have these attributes selected. These
we have these attributes selected. These are the bookmark properties on whether
are the bookmark properties on whether it's going to save things related to the
it's going to save things related to the data display or if it was related to the
data display or if it was related to the current page. So let's demo why this is
current page. So let's demo why this is important. Going back and selecting this
important. Going back and selecting this for column and bar charts filtered. If I
for column and bar charts filtered. If I were to select this one and then
were to select this one and then unselect data. So it's no longer
unselect data. So it's no longer selected. And then from there click
selected. And then from there click update because it's updating this
update because it's updating this bookmark. Now when I go to unfiltered
bookmark. Now when I go to unfiltered it's going to unfilter. And then when I
it's going to unfilter. And then when I go to filtered, it's not going to
go to filtered, it's not going to actually filter the data anymore because
actually filter the data anymore because we have data unchecked. So let's
we have data unchecked. So let's actually put that back where it needs to
actually put that back where it needs to be. We'll select data engineer, data
be. We'll select data engineer, data scientist, data analyst. We'll change
scientist, data analyst. We'll change this to data and then also click update.
this to data and then also click update. Now navigating between the two, they
Now navigating between the two, they work just fine. All right. Next up, what
work just fine. All right. Next up, what do we mean by display? Well, display
do we mean by display? Well, display deals with what visuals are shown or not
deals with what visuals are shown or not shown. Let's unfilter this data. Let's
shown. Let's unfilter this data. Let's say I wanted to insert in a slicer. So,
say I wanted to insert in a slicer. So, I'm going to put this bad boy right
I'm going to put this bad boy right here. I'm going to drag in the job title
here. I'm going to drag in the job title short column for it. Right now, we're
short column for it. Right now, we're going to change the settings and we're
going to change the settings and we're going to make it into tile. I'm going
going to make it into tile. I'm going make it a little bit bigger. Also, let's
make it a little bit bigger. Also, let's close out of this data pane.
close out of this data pane. Everything's getting sort of small.
Everything's getting sort of small. Anyway, as expected, right, I could use
Anyway, as expected, right, I could use this and holding control, I could select
this and holding control, I could select multiple different options that I want.
multiple different options that I want. But what happens if I wanted to use a
But what happens if I wanted to use a bookmark to control whether something
bookmark to control whether something like this visual uh is visible or not?
like this visual uh is visible or not? So let's first record a bookmark with
So let's first record a bookmark with this slicer available. I'll go ahead and
this slicer available. I'll go ahead and click add and then call this column and
click add and then call this column and bar slicer. Okay, so now this one's
bar slicer. Okay, so now this one's activated. And now I want to bookmark
activated. And now I want to bookmark where it's not visible. Well, I'm going
where it's not visible. Well, I'm going to go into the view ribbon and go to
to go into the view ribbon and go to selection. Also going to close down on
selection. Also going to close down on visualizations. Got too many panes over
visualizations. Got too many panes over here. Anyway, if you remember, we went
here. Anyway, if you remember, we went over selection pane previously. We can
over selection pane previously. We can hide or display certain options. So,
hide or display certain options. So, what I'm going to do is I'm going to go
what I'm going to do is I'm going to go ahead and hide it. And now, let's add
ahead and hide it. And now, let's add another bookmark and call this column
another bookmark and call this column and bar no slicer. So, now with the
and bar no slicer. So, now with the bookmark, I can toggle between being a
bookmark, I can toggle between being a slicer and no slicer. Now, visually,
slicer and no slicer. Now, visually, this is actually I don't really like
this is actually I don't really like this how this is done visually. So, I'm
this how this is done visually. So, I'm going to just show a quick little trick
going to just show a quick little trick how we can fix this. Going to insert.
how we can fix this. Going to insert. I'm going to insert in a shape,
I'm going to insert in a shape, specifically a rectangle. Make this bad
specifically a rectangle. Make this bad boy take up the entire view. Put this
boy take up the entire view. Put this underneath the slicer. So, the slicer is
underneath the slicer. So, the slicer is on top of it. And then for format shape,
on top of it. And then for format shape, we're going to go into the style, change
we're going to go into the style, change this to the color of black, and then
this to the color of black, and then change the transparency to something
change the transparency to something like 75%. Okay. So, it looks like, hey,
like 75%. Okay. So, it looks like, hey, it's popping out in front. I can insert
it's popping out in front. I can insert another shape behind it. Putting it
another shape behind it. Putting it behind the slicer itself. And for this
behind the slicer itself. And for this one, I'm going to change the color to
one, I'm going to change the color to just white. This one will leave
just white. This one will leave transparency at zero. All right. So now
transparency at zero. All right. So now for our bookmark for the slicer, I want
for our bookmark for the slicer, I want to update what it looks like. So I'm
to update what it looks like. So I'm going to click it and click update. Now
going to click it and click update. Now when I navigate between no slicer and
when I navigate between no slicer and slicer, that didn't work.
slicer, that didn't work. That didn't work because for no slicer,
That didn't work because for no slicer, I actually need to update this one as
I actually need to update this one as well to remove this shape and this
well to remove this shape and this shape. So, we'll update this one as
shape. So, we'll update this one as well. Now, slicer, no slicer. Now, let's
well. Now, slicer, no slicer. Now, let's add buttons to activate this. So, under
add buttons to activate this. So, under insert tab, under buttons, I'm just
insert tab, under buttons, I'm just going to use this one here on bookmarks.
going to use this one here on bookmarks. I made it slightly bigger. And then in
I made it slightly bigger. And then in it, we're going to navigate to the
it, we're going to navigate to the format button. And under action, I'm
format button. And under action, I'm going to change this bookmark to
going to change this bookmark to activate the slicer. So now whenever I
activate the slicer. So now whenever I click this, it activates the slicer, but
click this, it activates the slicer, but the button's still there. I actually
the button's still there. I actually want the button to disappear because we
want the button to disappear because we need to stick another button in that
need to stick another button in that place to make the slicer disappear.
place to make the slicer disappear. So with this, I'm going to hide this
So with this, I'm going to hide this button. And once again, I need to update
button. And once again, I need to update this slicer view. So I click three dots,
this slicer view. So I click three dots, clicked update. Now, navigating back
clicked update. Now, navigating back between the two, testing it out. Click
between the two, testing it out. Click the button. The button disappears. Okay.
the button. The button disappears. Okay. So, now let's add a button on here. For
So, now let's add a button on here. For this, we're just going to keep it
this, we're just going to keep it simple. We're going to add this back
simple. We're going to add this back arrow. And we'll go into formatting that
arrow. And we'll go into formatting that button. The action specifically, I want
button. The action specifically, I want it to go to a bookmark. And we want to
it to go to a bookmark. And we want to go to column and bar. No slicer. Now,
go to column and bar. No slicer. Now, testing this button out. I'm going to
testing this button out. I'm going to click it. And both buttons are
click it. And both buttons are appearing. Uh that means we need to on
appearing. Uh that means we need to on this visual hide the back arrow button
this visual hide the back arrow button and thus update this no slicer to make
and thus update this no slicer to make sure that includes it. Okay, this should
sure that includes it. Okay, this should be the final tweak for this. Yep, now I
be the final tweak for this. Yep, now I can use these buttons to navigate back
can use these buttons to navigate back and forth and I don't have to go to this
and forth and I don't have to go to this bookmarks pane. Now one major thing you
bookmarks pane. Now one major thing you may have noticed with this, let's say I
may have noticed with this, let's say I clicked open this and then I selected
clicked open this and then I selected data analyst, data engineers, data
data analyst, data engineers, data scientist and then clicked back. My data
scientist and then clicked back. My data resets. What the heck is going on here?
resets. What the heck is going on here? Well, as we demonstrated in the
Well, as we demonstrated in the unfiltered and then also the filtered
unfiltered and then also the filtered example, which apparently I need to
example, which apparently I need to update these as well, visuals. We'll get
update these as well, visuals. We'll get to that. We need to adjust what is going
to that. We need to adjust what is going on with the data uh metadata that's
on with the data uh metadata that's going on and being saved here.
going on and being saved here. Specifically, we don't want to keep
Specifically, we don't want to keep exactly this data in here. So, just to
exactly this data in here. So, just to make sure I'm clear, I have no slicer
make sure I'm clear, I have no slicer selected. From there, I'm going to
selected. From there, I'm going to uncheck data and then I'm going to click
uncheck data and then I'm going to click update. I'm going to do the same thing
update. I'm going to do the same thing now with the slicer. I'm going to
now with the slicer. I'm going to uncheck data and then with that click
uncheck data and then with that click update. So now whenever I'm working with
update. So now whenever I'm working with this and I select data analyst, data
this and I select data analyst, data engineer, data scientist and then close
engineer, data scientist and then close out of this, it stays because that no
out of this, it stays because that no slicer bookmark is not preserving the
slicer bookmark is not preserving the data state. I'm going to update the
data state. I'm going to update the filtered and unfiltered real quick. For
filtered and unfiltered real quick. For the filtered, I want to hide basically
the filtered, I want to hide basically all these different things that we had
all these different things that we had on here and then click update. For
on here and then click update. For unfiltered, I want to do the same thing
unfiltered, I want to do the same thing and then click update. Okay, this is a
and then click update. Okay, this is a great way. Now we can just cycle between
great way. Now we can just cycle between all these, make sure that it's working,
all these, make sure that it's working, everything's working fine. Looks like
everything's working fine. Looks like I'm sort of a silly. I didn't maintain
I'm sort of a silly. I didn't maintain the buttons as they needed to be.
the buttons as they needed to be. Specifically, that bookmark filter. I'm
Specifically, that bookmark filter. I'm going to just update that real quick on
going to just update that real quick on both of these. So, as you can see by
both of these. So, as you can see by that, this can get real finicky to make
that, this can get real finicky to make sure that you want everything to work
sure that you want everything to work properly and everything set up just
properly and everything set up just fine. So, that way there's nothing that
fine. So, that way there's nothing that is interfering with the other thing. So,
is interfering with the other thing. So, bookmarks can get really technical.
bookmarks can get really technical. Because of that, we got some practice
Because of that, we got some practice problems for you to now go through and
problems for you to now go through and test your capabilities with creating
test your capabilities with creating buttons and also with bookmarks. With
buttons and also with bookmarks. With that, we now have all the skills
that, we now have all the skills necessary to dive into our first
necessary to dive into our first project. And for that, we'll be building
project. And for that, we'll be building a data science dashboard with this data
a data science dashboard with this data set we've been working with and a lot of
set we've been working with and a lot of the visuals we've already built. All
the visuals we've already built. All right, with that, I'll see you in the
right, with that, I'll see you in the next one.
Welcome to this first of three lessons in building our first project with
in building our first project with PowerBI. In this lesson and the next
PowerBI. In this lesson and the next lesson, we'll be building the first and
lesson, we'll be building the first and second page of our dashboard. And then
second page of our dashboard. And then in the final lesson, we'll be going
in the final lesson, we'll be going through how we can share it via
through how we can share it via something like PowerBI service or even
something like PowerBI service or even something like GitHub.
So before we get into actually building this dashboard, we need to understand
this dashboard, we need to understand what are some basic or best practices to
what are some basic or best practices to implement to create a dashboard that
implement to create a dashboard that people are actually going to use. I can
people are actually going to use. I can tell you from personal experience that a
tell you from personal experience that a lot of dashboards that I built,
lot of dashboards that I built, especially my younger days, that I
especially my younger days, that I didn't have these type of principles in
didn't have these type of principles in mind, I guarantee you they're not in use
mind, I guarantee you they're not in use today because of that. And specifically,
today because of that. And specifically, it starts and also ends with two main
it starts and also ends with two main questions that you should always be
questions that you should always be asking yourself. What problem are we
asking yourself. What problem are we trying to solve with this dashboard? And
trying to solve with this dashboard? And who are we designing this dashboard for?
who are we designing this dashboard for? You may think that you have the newest
You may think that you have the newest and greatest dashboard built, but if
and greatest dashboard built, but if your end consumer, your stakeholder
your end consumer, your stakeholder doesn't have the same concerns or same
doesn't have the same concerns or same problems that they think are being had,
problems that they think are being had, they're not going to be using the
they're not going to be using the dashboard. This is a great example, or
dashboard. This is a great example, or actually I should say a bad example
actually I should say a bad example specifically how somebody built a
specifically how somebody built a dashboard and didn't think of those two
dashboard and didn't think of those two questions. I mean, just looking at it,
questions. I mean, just looking at it, who is it? Who do you think this is even
who is it? Who do you think this is even intended for and what problem are they
intended for and what problem are they trying to solve? This is a dashboard I
trying to solve? This is a dashboard I found online and it's a dashboard that
found online and it's a dashboard that obviously deals with something around
obviously deals with something around sales for a company. But even as a user
sales for a company. But even as a user myself, where should I be looking and
myself, where should I be looking and what should I be drawing my attention
what should I be drawing my attention to? From a design perspective, there's
to? From a design perspective, there's entirely too many colors. And for that
entirely too many colors. And for that pie chart up there or that donut chart,
pie chart up there or that donut chart, once again, you should never have that
once again, you should never have that many values inside of there. All right,
many values inside of there. All right, this next example, they're going to get
this next example, they're going to get better by the way as we go along. This
better by the way as we go along. This example, not too bad. This dashboard is
example, not too bad. This dashboard is obviously being used for some
obviously being used for some stakeholders within supply chain and
stakeholders within supply chain and sales that want to monitor the
sales that want to monitor the performance over time and they have a
performance over time and they have a specific attributes that they're looking
specific attributes that they're looking at. From a design perspective though,
at. From a design perspective though, I'm going to say this has once again a
I'm going to say this has once again a little bit too many colors. Mostly I'm
little bit too many colors. Mostly I'm getting drawn to those portions that are
getting drawn to those portions that are red, such as that profit, then that
red, such as that profit, then that ranking overview at the bottom. But red
ranking overview at the bottom. But red doesn't mean that it's bad. It's just
doesn't mean that it's bad. It's just how they colored it. Not really a fan of
how they colored it. Not really a fan of it. I do however like that it is dark
it. I do however like that it is dark mode. Next up is this one on call center
mode. Next up is this one on call center dashboard. And easily I can see from
dashboard. And easily I can see from this this is monitoring how active a
this this is monitoring how active a call center is and specifically what
call center is and specifically what areas are most active. So this is
areas are most active. So this is probably made for some sort of manager
probably made for some sort of manager within a call center to monitor
within a call center to monitor performance and see if there's any
performance and see if there's any irregularities. I'm liking the design
irregularities. I'm liking the design aspect from this. It's very simple. They
aspect from this. It's very simple. They kept simple color palettes to draw your
kept simple color palettes to draw your eye and attention into darker colors.
eye and attention into darker colors. Although I would argue that some of the
Although I would argue that some of the lighter colors are a little too
lighter colors are a little too distracting, but overall nice little
distracting, but overall nice little view. Oh, and it has a little dark and
view. Oh, and it has a little dark and light mode that you can switch between.
light mode that you can switch between. All right, last one's probably my most
All right, last one's probably my most favorite. In this one, we can see that
favorite. In this one, we can see that clearly we're monitoring some sort of
clearly we're monitoring some sort of web traffic. And we have the cards up at
web traffic. And we have the cards up at the top in order to draw our attention
the top in order to draw our attention into the most key metrics. and then
into the most key metrics. and then visuals underneath this in order to
visuals underneath this in order to reinforce what's going above. I really
reinforce what's going above. I really like this type of design and I'm going
like this type of design and I'm going to recommend it. I'm really liking these
to recommend it. I'm really liking these sessions and page views cuz we can see
sessions and page views cuz we can see we do have some anomalies here in some
we do have some anomalies here in some portions. So, that would queue me in as
portions. So, that would queue me in as a manager of this that I'd want to maybe
a manager of this that I'd want to maybe go and investigate those areas. And why
go and investigate those areas. And why we have it's probably at the same time
we have it's probably at the same time why we have these bounce rates and page
why we have these bounce rates and page exits during that and probably we have
exits during that and probably we have this large spike right here. Anyway, the
this large spike right here. Anyway, the simpler the better. Really love the
simpler the better. Really love the simplicity of this.
So, getting into the planning of our dashboard, we want to first start out by
dashboard, we want to first start out by looking at and answering those two
looking at and answering those two questions that I previously was
questions that I previously was scrutinizing. First is who are we
scrutinizing. First is who are we designing this for? Specifically, we're
designing this for? Specifically, we're going to design this for job seekers,
going to design this for job seekers, job transitioners, or swappers.
job transitioners, or swappers. Basically, somebody looking for a
Basically, somebody looking for a promotion within a company. and
promotion within a company. and specifically those that are working in
specifically those that are working in data science because I got data on data
data science because I got data on data science jobs. And what problem are we
science jobs. And what problem are we trying to solve? Well, those look for
trying to solve? Well, those look for roles often struggle because information
roles often struggle because information about the job market scattered
about the job market scattered everywhere. There's no single location
everywhere. There's no single location to get an overall trend of the market,
to get an overall trend of the market, typical compensation levels, and even
typical compensation levels, and even job quality. So that's what our
job quality. So that's what our dashboard is aiming to solve because we
dashboard is aiming to solve because we could go to something like LinkedIn,
could go to something like LinkedIn, search for a job like data analyst and
search for a job like data analyst and yeah it provides an overview of
yeah it provides an overview of different jobs available and an amount
different jobs available and an amount of results but there's nothing related
of results but there's nothing related to trends expected pay and whatnot. So
to trends expected pay and whatnot. So we're going to be aiming to solve this.
we're going to be aiming to solve this. So, anytime you're starting out, I
So, anytime you're starting out, I recommend actually going and if you
recommend actually going and if you will, drawing out or just giving a rough
will, drawing out or just giving a rough sketch of what you want to accomplish
sketch of what you want to accomplish with your dashboard. And if you have
with your dashboard. And if you have stakeholders available, you can show
stakeholders available, you can show them what you're thinking and g then get
them what you're thinking and g then get direct feedback. So, make sure you're
direct feedback. So, make sure you're not going down a wrong avenue. for this
not going down a wrong avenue. for this dashboard. I did this beforehand and put
dashboard. I did this beforehand and put together a rough sketch of some things
together a rough sketch of some things that I'd like to have available on a
that I'd like to have available on a dashboard for me to have access to. I've
dashboard for me to have access to. I've been in a position of job searching. So,
been in a position of job searching. So, I really put on that lens to try to
I really put on that lens to try to analyze this and dissect if this is how
analyze this and dissect if this is how I wanted it. Key things with this is I
I wanted it. Key things with this is I like to keep it symmetrical, right? So,
like to keep it symmetrical, right? So, I have all of my cards up at the top. I
I have all of my cards up at the top. I have the graphs equally spaced and
have the graphs equally spaced and equally made. I want to keep the visuals
equally made. I want to keep the visuals as simple as possible. So that's why I
as simple as possible. So that's why I have the line and the bar charts on the
have the line and the bar charts on the left. We'll have a table and scatter
left. We'll have a table and scatter plot on the right hand side, which I
plot on the right hand side, which I feel is less likely for them to look
feel is less likely for them to look towards, but also we'll have that key
towards, but also we'll have that key information, especially in that table if
information, especially in that table if they want to export it into Excel. So
they want to export it into Excel. So let's get into building this bad boy.
let's get into building this bad boy. We're going to be doing a rough draft
We're going to be doing a rough draft first. We're going to be starting from
first. We're going to be starting from the top and then building down.
So, in your current workbook, we're going to stay in here because we're
going to stay in here because we're going to copy a lot of different
going to copy a lot of different visualizations from it and also use that
visualizations from it and also use that same data set that we cleaned up. And
same data set that we cleaned up. And I'm going to create a new page and we're
I'm going to create a new page and we're going to call it data jobs dashboard.
going to call it data jobs dashboard. We'll leave the page all the way at the
We'll leave the page all the way at the end. When we're done building this
end. When we're done building this dashboard, we're going to go ahead and
dashboard, we're going to go ahead and delete all these pages and save it as it
delete all these pages and save it as it no own PowerBI file. But for now, we'll
no own PowerBI file. But for now, we'll just keep it all together. Anyway, first
just keep it all together. Anyway, first thing I'm going to do is put a title in
thing I'm going to do is put a title in here. So, I'm going to insert in a text
here. So, I'm going to insert in a text box. And inside of it, I'm going to put
box. And inside of it, I'm going to put data jobs dashboard. And I just
data jobs dashboard. And I just formatted it to be a little bit bigger.
formatted it to be a little bit bigger. Next up, I'm going to insert a slicer.
Next up, I'm going to insert a slicer. So, I can go to our slicers pane and I'm
So, I can go to our slicers pane and I'm going to select this one here on the job
going to select this one here on the job title. Going to insert it in. In this
title. Going to insert it in. In this case, I want to keep them separate
case, I want to keep them separate because they're their own dashboard. So,
because they're their own dashboard. So, we're not going to sync. And I'm going
we're not going to sync. And I'm going to minimize some of these panes over
to minimize some of these panes over here. So, I can come into here anyway. I
here. So, I can come into here anyway. I want to change the format of this slicer
want to change the format of this slicer specifically. I just want it to be a
specifically. I just want it to be a drop down. I don't want it to be too
drop down. I don't want it to be too crazy. All right, so that's good. Now,
crazy. All right, so that's good. Now, let's move into putting the cards up.
let's move into putting the cards up. Remember, we're going to be doing job
Remember, we're going to be doing job count, job rating, yearly salary, and
count, job rating, yearly salary, and hourly salary. I also have it in this
hourly salary. I also have it in this format because job count, these graphs
format because job count, these graphs underneath it are going to correlate to
underneath it are going to correlate to the count. And then whereas the salary,
the count. And then whereas the salary, everything underneath it, the scatter
everything underneath it, the scatter plot that deals with salary and the
plot that deals with salary and the tables are going to deal with salary.
tables are going to deal with salary. So, I leave that aside. So, it makes it
So, I leave that aside. So, it makes it symmetrical but also intuitive. On the
symmetrical but also intuitive. On the cards page, I'm going to copy this one
cards page, I'm going to copy this one that we have on median year salary. Ctrl
that we have on median year salary. Ctrl + C. And then paste it in over here. I'm
+ C. And then paste it in over here. I'm going to align it towards the center
going to align it towards the center because I know I want it over here. And
because I know I want it over here. And we'll put it right here. Okay. I'm going
we'll put it right here. Okay. I'm going to copy this one and then adjust the
to copy this one and then adjust the spacing. I also adjust the width a
spacing. I also adjust the width a little bit. And then I'm going to go
little bit. And then I'm going to go ahead and copy this. Paste another one
ahead and copy this. Paste another one right here. And then another one right
right here. And then another one right here. First one. Remember, we want job
here. First one. Remember, we want job count. So I'm going take that job tile
count. So I'm going take that job tile short. throw it into here. Change
short. throw it into here. Change aggregation account and then this to job
aggregation account and then this to job count. Next thing I want that star
count. Next thing I want that star rating for this. So I'm going to take
rating for this. So I'm going to take the salary star rating, drag it into
the salary star rating, drag it into here. And this one looks like it's
here. And this one looks like it's formatted good. And the only other one
formatted good. And the only other one we need to change this one from median
we need to change this one from median yearly salary to median hourly salary.
yearly salary to median hourly salary. Not too bad. Not liking how this number
Not too bad. Not liking how this number is formatted here. So under format or
is formatted here. So under format or visual for this one, going into the
visual for this one, going into the values, changing the settings to just
values, changing the settings to just job count itself. We'll set the value uh
job count itself. We'll set the value uh the value decimal places to zero. Now
the value decimal places to zero. Now let's put some visuals in here. We'll
let's put some visuals in here. We'll start with top left getting these job
start with top left getting these job count over time on our line and area
count over time on our line and area page. This one's good enough. We'll take
page. This one's good enough. We'll take a control C of this and I'll paste it
a control C of this and I'll paste it right in. Next up, I want our job counts
right in. Next up, I want our job counts per job title. This is the closest one I
per job title. This is the closest one I can find on our column and bar chart
can find on our column and bar chart page. So, I'm going to copy this. We'll
page. So, I'm going to copy this. We'll just have to alter it. And I'll paste
just have to alter it. And I'll paste this in down here, squeezing it in. And
this in down here, squeezing it in. And then we'll change this from using that
then we'll change this from using that median yearly salary to instead using
median yearly salary to instead using the count of jobs. Next up is that
the count of jobs. Next up is that scatter plot in the top rightand corner.
scatter plot in the top rightand corner. If you navigate to that common charts
If you navigate to that common charts page, we're going to be using this one.
page, we're going to be using this one. I'm going to copy it, then paste it
I'm going to copy it, then paste it right into here. Format where it needs
right into here. Format where it needs to go. All right, the final one is our
to go. All right, the final one is our table or more specifically our matrix
table or more specifically our matrix that we made. So I'm going to go ahead
that we made. So I'm going to go ahead and copy this and then we're going to
and copy this and then we're going to put it down at the bottom right hand
put it down at the bottom right hand corner. All right. So, not so bad for a
corner. All right. So, not so bad for a rough draft. We have everything that we
rough draft. We have everything that we want inside of here. If I wanted to, I
want inside of here. If I wanted to, I could filter down for something like
could filter down for something like business analyst. And it shows us
business analyst. And it shows us everything we need for this.
Now, let's get this bad boy cleaned up now. And here's a look at where we're
now. And here's a look at where we're going to finally get to. Specifically, I
going to finally get to. Specifically, I like adding backgrounds and boxes to
like adding backgrounds and boxes to sort of box things off to draw people's
sort of box things off to draw people's attention in to where they need to go to
attention in to where they need to go to and look. In this case, once again, I'm
and look. In this case, once again, I'm keeping it very symmetrical. But like I
keeping it very symmetrical. But like I said, like with this job count, this
said, like with this job count, this area deals with counts and this side
area deals with counts and this side really deals with salary. So that's why
really deals with salary. So that's why I've designed it in this manner. Anyway,
I've designed it in this manner. Anyway, all this is doing is inserting shapes
all this is doing is inserting shapes into here. And specifically, we're
into here. And specifically, we're inserting it behind the visual. So going
inserting it behind the visual. So going into insert into shapes, we're going to
into insert into shapes, we're going to insert in a rounded rectangle. I'm going
insert in a rounded rectangle. I'm going to put it over on top of the area that
to put it over on top of the area that we want. We'll adjust the formatting
we want. We'll adjust the formatting here in a little bit, but first with
here in a little bit, but first with under format shapes under the style, you
under format shapes under the style, you know, I like that light blue. So, we're
know, I like that light blue. So, we're going to start with light blue. Also, I
going to start with light blue. Also, I like shadows. So, we're going to add a
like shadows. So, we're going to add a shadow to this. And it also makes it a
shadow to this. And it also makes it a little bit smaller and not touching the
little bit smaller and not touching the edges. Now, with this selected, I've
edges. Now, with this selected, I've formatted enough. I'm going to control C
formatted enough. I'm going to control C it and then Ctrl +V. I'm going go
it and then Ctrl +V. I'm going go through and just put this over all the
through and just put this over all the different visuals in here. We'll then
different visuals in here. We'll then adjust the order after this. Not too
adjust the order after this. Not too bad. going into view and then selection.
bad. going into view and then selection. First of all, I'm going to select all of
First of all, I'm going to select all of them together because I want to group
them together because I want to group them just to make it easier. I'm
them just to make it easier. I'm pressing control while I do this. And
pressing control while I do this. And then I'm going to click the three dots
then I'm going to click the three dots and click group. Okay, so now it's all
and click group. Okay, so now it's all one group. I'll then name this to
one group. I'll then name this to background. And then I can take the
background. And then I can take the background all the way to the bottom of
background all the way to the bottom of the selection. So that way it puts it
the selection. So that way it puts it behind. And now you're like, Luke, what
behind. And now you're like, Luke, what happened? It disappeared. Well, as you
happened? It disappeared. Well, as you can see through the cracks, it is there.
can see through the cracks, it is there. Um, but we have to actually remove the
Um, but we have to actually remove the backgrounds of all these other things.
backgrounds of all these other things. What do we mean by that? Okay, let's
What do we mean by that? Okay, let's select a card. I'm going to minimize
select a card. I'm going to minimize this and go into format visual. So,
this and go into format visual. So, inside of here, I'm going to just
inside of here, I'm going to just actually search and I'm going to search
actually search and I'm going to search for background. Underneath effects, I'm
for background. Underneath effects, I'm going to turn off this background. And
going to turn off this background. And then also on the cards itself, I'm gonna
then also on the cards itself, I'm gonna turn off that background. And we got to
turn off that background. And we got to go through and do this for all of them
go through and do this for all of them as well. Turning off the effects
as well. Turning off the effects background and then the cards
background and then the cards background. For the graphs and visuals,
background. For the graphs and visuals, it should be only the effects background
it should be only the effects background that you need to turn off. But for the
that you need to turn off. But for the matrix, we need to not only do the
matrix, we need to not only do the effects background, but also you can see
effects background, but also you can see there's other white behind it. And for
there's other white behind it. And for it, we need to go to layout and style
it, we need to go to layout and style presets. The style is on default right
presets. The style is on default right now. We're going to change it to none.
now. We're going to change it to none. Now, what I'm going to do is just go
Now, what I'm going to do is just go through and adjust the size of all this
through and adjust the size of all this to make sure they fit within their
to make sure they fit within their appropriate squares. All right. So,
appropriate squares. All right. So, looking good. Not too bad. If you wanted
looking good. Not too bad. If you wanted to dive into one of these, such as we
to dive into one of these, such as we did before, we can enter obviously focus
did before, we can enter obviously focus mode and we can still see it everything
mode and we can still see it everything visually. But the only thing that I'm
visually. But the only thing that I'm seeing left is how these icons have this
seeing left is how these icons have this white value and it can get sort of
white value and it can get sort of distracting from what's going on there.
distracting from what's going on there. These are controlled under general and
These are controlled under general and header icon. You can't just toggle them
header icon. You can't just toggle them on or off, unfortunately. You have to
on or off, unfortunately. You have to actually change the transparency to 100%
actually change the transparency to 100% to make it sort of hide a little bit
to make it sort of hide a little bit better. So, I'm going to go through and
better. So, I'm going to go through and just hide all these different ones. All
just hide all these different ones. All right, not too bad. Going to go ahead
right, not too bad. Going to go ahead and save this.
and save this. We're going to stop right there for this
We're going to stop right there for this page. In the next lesson, if you will,
page. In the next lesson, if you will, we'll be building the second page for
we'll be building the second page for this. and we're going to be using a new
this. and we're going to be using a new feature that we haven't discussed yet
feature that we haven't discussed yet and that's drill through. There's no
and that's drill through. There's no practice problems for this lesson or any
practice problems for this lesson or any lessons in the project. And with that,
lessons in the project. And with that, see you in the next one.
All right, welcome to the second of three videos in this project section.
three videos in this project section. We're now going to get into building our
We're now going to get into building our drill through page. And you're probably
drill through page. And you're probably like, what the heck is a drill through?
like, what the heck is a drill through? So, let's actually demonstrate it in
So, let's actually demonstrate it in action. Here I am in our final dashboard
action. Here I am in our final dashboard right here. And right now users can go
right here. And right now users can go through and see different things. And
through and see different things. And typically they're going to want to look
typically they're going to want to look in or dive in deeper to something. Let's
in or dive in deeper to something. Let's say I'm a data engineer and I come in
say I'm a data engineer and I come in here and I select that engineer to find
here and I select that engineer to find out different values about it. Well, I
out different values about it. Well, I want to learn more. Well, if you notice
want to learn more. Well, if you notice this button up at the top became well,
this button up at the top became well, it moved from a uh grade out to actually
it moved from a uh grade out to actually ungrade out, if you will, or a visible.
ungrade out, if you will, or a visible. And so now it says drill through to job
And so now it says drill through to job title. And what I can do is press
title. And what I can do is press controlclick to it. And now we're
controlclick to it. And now we're directed to our drill through page. And
directed to our drill through page. And this is what we're going to be building
this is what we're going to be building in this course specifically for this
in this course specifically for this lesson. Anyway, with it, this has
lesson. Anyway, with it, this has specific metrics that I feel are more
specific metrics that I feel are more applicable at a job title level. And
applicable at a job title level. And remember, we selected data engineer. We
remember, we selected data engineer. We have that at the top. Then we have
have that at the top. Then we have things like the hourly and yearly
things like the hourly and yearly salary, the different percentages for
salary, the different percentages for all the different attributes, and then
all the different attributes, and then some different visualizations as well.
some different visualizations as well. Anyway, if we want to navigate back to
Anyway, if we want to navigate back to home, we can click this icon to go back,
home, we can click this icon to go back, and bam, we're back at the data jobs
and bam, we're back at the data jobs dashboard, and everything's cleared. So,
dashboard, and everything's cleared. So, let's actually get into building this
let's actually get into building this drill through.
drill through. So, in our PowerBI file, I'm going to
So, in our PowerBI file, I'm going to create a new page, and I'm going to call
create a new page, and I'm going to call it job title drill through. First thing
it job title drill through. First thing I'm going to stick in here is a card.
I'm going to stick in here is a card. similar to the last thing up at the top
similar to the last thing up at the top that displays what is the job title
that displays what is the job title we're drilling through to. So, I'm just
we're drilling through to. So, I'm just going to come in here and we're going to
going to come in here and we're going to steal it from our first dashboard, at
steal it from our first dashboard, at least the formatting for it, and paste
least the formatting for it, and paste it up here in the top. Now, for this,
it up here in the top. Now, for this, right, I want the job title that it's
right, I want the job title that it's filtered to to displaying in this card.
filtered to to displaying in this card. So, I'm going to drag this job title
So, I'm going to drag this job title short column over into the data to
short column over into the data to replace it. And I'm going to call this
replace it. And I'm going to call this job title Joe through since that's the
job title Joe through since that's the name of our page. Anyway, right now I'm
name of our page. Anyway, right now I'm aggregating to the first value that
aggregating to the first value that appears and right now it's business
appears and right now it's business analyst. So let's actually experiment
analyst. So let's actually experiment with or actually implement our drill
with or actually implement our drill through. So you may have noticed before
through. So you may have noticed before on the visualizations pane if I actually
on the visualizations pane if I actually scroll all the way down they have this
scroll all the way down they have this section here on drill through and this
section here on drill through and this says hey you can add drill through
says hey you can add drill through fields here. For example, we want to
fields here. For example, we want to drill through based on well what this
drill through based on well what this card has too, but that job title short
card has too, but that job title short column. And inside of it, it allows you
column. And inside of it, it allows you to filter the data for what you want.
to filter the data for what you want. We're going to leave everything as is.
We're going to leave everything as is. So overall, you can see nothing really
So overall, you can see nothing really changed on this page. Well, something
changed on this page. Well, something that did change. We got this back arrow
that did change. We got this back arrow up at the top lefthand corner. But this
up at the top lefthand corner. But this now is where the magic happens. I can go
now is where the magic happens. I can go to data jobs dashboard and something
to data jobs dashboard and something like data engineer. I can go ahead and
like data engineer. I can go ahead and select it. Right, we don't have a button
select it. Right, we don't have a button just yet. But what I can do is I can
just yet. But what I can do is I can rightclick it and inside of this popup
rightclick it and inside of this popup it says drill through. And then it says
it says drill through. And then it says we can drill through to the page of job
we can drill through to the page of job title drill through. And I'm now taken
title drill through. And I'm now taken to that page. And that page is filtered
to that page. And that page is filtered for data engineer. One note, you can
for data engineer. One note, you can selecting this card itself and then
selecting this card itself and then scrolling on down to drill through.
scrolling on down to drill through. Right now we have keep all filters on
Right now we have keep all filters on for the drill through. So basically the
for the drill through. So basically the filter on the other page that cross
filter on the other page that cross filters applied to here. And any other
filters applied to here. And any other filters that we may have on that page
filters that we may have on that page are applied to this page. I like to keep
are applied to this page. I like to keep it on. Keep it on. Oh, and then to demo
it on. Keep it on. Oh, and then to demo we still have that they we have that
we still have that they we have that arrow up there. The arrow then takes us
arrow up there. The arrow then takes us back to the previous page in the report
back to the previous page in the report that we came from. Now, this isn't
that we came from. Now, this isn't specific. We didn't add anything to the
specific. We didn't add anything to the data jobs dashboard. Just a demo. If I
data jobs dashboard. Just a demo. If I went to that column and bar section, we
went to that column and bar section, we could do the same thing inside of here.
could do the same thing inside of here. Drill through to that job title. Drill
Drill through to that job title. Drill through. And then we did it for senior
through. And then we did it for senior data scientist. So, I could navigate
data scientist. So, I could navigate back to that as well. All right. So,
back to that as well. All right. So, let's start building out this page.
let's start building out this page. We're going to start at the top building
We're going to start at the top building out these visuals and then working our
out these visuals and then working our way down into the map, bar chart, and
way down into the map, bar chart, and also the tree map. I'm going to take our
also the tree map. I'm going to take our yearly salary gauge and copy it from our
yearly salary gauge and copy it from our cards page. Put it all in. Format it
cards page. Put it all in. Format it down. Duplicate this and then change
down. Duplicate this and then change everything so that way it's hourly
everything so that way it's hourly salary. Don't forget also to change the
salary. Don't forget also to change the title. Next up are those fancy dancy
title. Next up are those fancy dancy doughnut charts we made in the common
doughnut charts we made in the common charts lesson. I'm going to go ahead and
charts lesson. I'm going to go ahead and copy this and then from there duplicate
copy this and then from there duplicate it three times. I had to move things
it three times. I had to move things around. It's not going to be as
around. It's not going to be as symmetrical as I want it. I'm also going
symmetrical as I want it. I'm also going to change these titles now. I don't want
to change these titles now. I don't want them all work from home. So change it to
them all work from home. So change it to no degree mentioned health insurance.
no degree mentioned health insurance. Now, we need to actually adjust the
Now, we need to actually adjust the values in here to actually use what
values in here to actually use what we're supposed to be using. All right,
we're supposed to be using. All right, not too bad. I messed up the coloring
not too bad. I messed up the coloring here. I need to just clean it up while
here. I need to just clean it up while we're in this. Specifically, I'm going
we're in this. Specifically, I'm going to change all the true values to this
to change all the true values to this blue color and the false values to like
blue color and the false values to like a lighter gray. That way, these all have
a lighter gray. That way, these all have a similar type format. All right, three
a similar type format. All right, three more visuals left. I'm going to go to
more visuals left. I'm going to go to the map chart. I'm going to go in and
the map chart. I'm going to go in and steal this one here for where we were
steal this one here for where we were looking at the mentioning of the job
looking at the mentioning of the job postings. Mention degree. We're actually
postings. Mention degree. We're actually going to remove that from the legend. Go
going to remove that from the legend. Go ahead and put that in there and then
ahead and put that in there and then remove that from the legend so it's only
remove that from the legend so it's only showing job counting and give it the
showing job counting and give it the title where are jobs globally. Next up
title where are jobs globally. Next up from the common charts lecture I'm going
from the common charts lecture I'm going to steal this one are what are the type
to steal this one are what are the type of data jobs and put that one in right
of data jobs and put that one in right here into the center bottom right. Last
here into the center bottom right. Last one that needed this one we don't have
one that needed this one we don't have already. I'm going to insert in a stack
already. I'm going to insert in a stack bar chart. Make it fill in the remaining
bar chart. Make it fill in the remaining value. For this one, I want to look at
value. For this one, I want to look at that job via column, specifically the
that job via column, specifically the count, like where are the job postings.
count, like where are the job postings. As we can see, LinkedIn is the top one.
As we can see, LinkedIn is the top one. And then I update this to what platform
And then I update this to what platform has most jobs along with changing this
has most jobs along with changing this one to what are the types of jobs. So,
one to what are the types of jobs. So, this has most what we want. Let's
this has most what we want. Let's actually test it out. We're going to go
actually test it out. We're going to go back to the data jobs dashboard. And we
back to the data jobs dashboard. And we can now click on this. And if we want to
can now click on this. And if we want to rightclick, drill through to the job
rightclick, drill through to the job title uh through page. Now, we're
title uh through page. Now, we're looking at everything for data
looking at everything for data engineers. can see where they're
engineers. can see where they're located, what platform we go to, and
located, what platform we go to, and what type. Not too bad. I wouldn't mind
what type. Not too bad. I wouldn't mind now going back here. We do want a button
now going back here. We do want a button up here because most users are not going
up here because most users are not going to be intuitive enough to think that,
to be intuitive enough to think that, hey, I can right click and go to the
hey, I can right click and go to the drill through. So, under the insert tab,
drill through. So, under the insert tab, I'm going to go to buttons. And for
I'm going to go to buttons. And for this, we're going to insert a blank
this, we're going to insert a blank button that's going to be put up here.
button that's going to be put up here. We'll then go ahead and now format it.
We'll then go ahead and now format it. Now, we'll go into format button. We're
Now, we'll go into format button. We're going to turn on the action itself.
going to turn on the action itself. Specifically, we want it to drill
Specifically, we want it to drill through. So, we'll change this from back
through. So, we'll change this from back to drill through. And for the
to drill through. And for the destination, we need to make sure we
destination, we need to make sure we select job title drill through. Okay.
select job title drill through. Okay. So, now just testing this out. I click
So, now just testing this out. I click data engineer. It's no longer grayed
data engineer. It's no longer grayed out. Clicking control. It navigates me
out. Clicking control. It navigates me to this page. And I can navigate back.
to this page. And I can navigate back. But this button, we don't need to just
But this button, we don't need to just leave grayed out. Let's actually format
leave grayed out. Let's actually format it by making it into a round rectangle.
it by making it into a round rectangle. Turning on the fill and making it
Turning on the fill and making it obviously to a light blue. And then
obviously to a light blue. And then turning on the shadow. Oh, we obviously
turning on the shadow. Oh, we obviously want the text on in there. And I'm going
want the text on in there. And I'm going crank up the text size that says drill
crank up the text size that says drill through to job title. I'll even make it
through to job title. I'll even make it bold. Okay. So now, whenever we're
bold. Okay. So now, whenever we're inside of here, if I click on something
inside of here, if I click on something like that, engineer, boom, it's popping
like that, engineer, boom, it's popping up. Press control, drill through to job
up. Press control, drill through to job title, and I can navigate back if I want
title, and I can navigate back if I want to.
to. All right. So, similar to that last page
All right. So, similar to that last page we did, we need to now clean this up. I
we did, we need to now clean this up. I want to put some like we did in this
want to put some like we did in this one. Put the borders and the background
one. Put the borders and the background behind it. So, I'm going to go ahead and
behind it. So, I'm going to go ahead and copy this. Press Ctrl + C and then paste
copy this. Press Ctrl + C and then paste that into here. We're going to have to
that into here. We're going to have to reformat all the different sizes in
reformat all the different sizes in here. First things first, I'm going to
here. First things first, I'm going to go into the view tab and open up the
go into the view tab and open up the selections pane. We're also going to
selections pane. We're also going to close these on downs to make a bigger
close these on downs to make a bigger view. Anyway, remember we named it
view. Anyway, remember we named it background for this. I don't need these
background for this. I don't need these top two in here. So, what I'm going to
top two in here. So, what I'm going to do is just select ungroup. And then
do is just select ungroup. And then we're just going to go ahead and
we're just going to go ahead and actually delete it then by removing it.
actually delete it then by removing it. Okay. Now, these are ungrouped. I can
Okay. Now, these are ungrouped. I can just drag these into position where I
just drag these into position where I want them. All right. Not too bad.
want them. All right. Not too bad. Pressing control. I want to group these
Pressing control. I want to group these all back together. I rightcicked it.
all back together. I rightcicked it. Plus group. Renamed again to background.
Plus group. Renamed again to background. And then move all the way to the back.
And then move all the way to the back. It looks like I missed a shape. I'm
It looks like I missed a shape. I'm going to go ahead and just drag this on
going to go ahead and just drag this on down and then open up background and
down and then open up background and throw it inside of there because
throw it inside of there because apparently I forgot it. Okay, like last
apparently I forgot it. Okay, like last time, we need to remove these white
time, we need to remove these white backgrounds on here. So, going into each
backgrounds on here. So, going into each one of these visuals themselves, opening
one of these visuals themselves, opening up that visualization pane and then in
up that visualization pane and then in the search bar, putting in background,
the search bar, putting in background, I'm going to turn off the background
I'm going to turn off the background effects for these. Getting to the map, I
effects for these. Getting to the map, I was able to do that as well with
was able to do that as well with background effects. This one also. And
background effects. This one also. And then finally, our tree map. Okay, these
then finally, our tree map. Okay, these all need to get resized now to fit in
all need to get resized now to fit in there appropriately. Like last time, I
there appropriately. Like last time, I don't like these header icons with this
don't like these header icons with this color here. So, I'm going to make the
color here. So, I'm going to make the transparency 100%. And do this for all
transparency 100%. And do this for all of these. All right. So, boom. Let's
of these. All right. So, boom. Let's test this bad boy out. We're going to
test this bad boy out. We're going to navigate back. Okay. Inside of our data
navigate back. Okay. Inside of our data jobs dashboard, if we want to dive into
jobs dashboard, if we want to dive into something like data analyst, we can see
something like data analyst, we can see the key statistics here. And then diving
the key statistics here. And then diving into the drill through itself, I can see
into the drill through itself, I can see that just for data analyst, what are all
that just for data analyst, what are all the different metrics for it? And if I
the different metrics for it? And if I wanted to, I can filter down even
wanted to, I can filter down even further inside of here. All right, so
further inside of here. All right, so that wraps up what we're going to be
that wraps up what we're going to be doing for building out this first
doing for building out this first project. In the next lesson, we're going
project. In the next lesson, we're going to be jumping into actually how we can
to be jumping into actually how we can share it using PowerBI service. And if
share it using PowerBI service. And if you don't have that or you want to do a
you don't have that or you want to do a different option, we're going to have
different option, we're going to have GitHub as well. With that, I'll see you
GitHub as well. With that, I'll see you there. All
right, welcome to this lesson on going through how we're going to go share this
through how we're going to go share this first dashboard. And first of all,
first dashboard. And first of all, congratulations for completing this
congratulations for completing this first dashboard. It's quite an
first dashboard. It's quite an accomplishment. Now, this video is
accomplishment. Now, this video is completely optional. You can decide if
completely optional. You can decide if you want to go through it or not.
you want to go through it or not. Basically, at the beginning, I'm going
Basically, at the beginning, I'm going to go over what are the different
to go over what are the different options, and then the majority of it is
options, and then the majority of it is going to be spent on how we can actually
going to be spent on how we can actually set up and share your project on GitHub.
set up and share your project on GitHub. But if you don't want to share your work
But if you don't want to share your work and potentially get a new job with
and potentially get a new job with higher pay, feel free to skip to the
higher pay, feel free to skip to the next chapter on Power Query.
So, let's go over these three options that I'm going to recommend for how you
that I'm going to recommend for how you can go about sharing your dashboard. The
can go about sharing your dashboard. The first one is the most recommended option
first one is the most recommended option and I think that you'll get the most
and I think that you'll get the most visibility with it. Specifically, it
visibility with it. Specifically, it involves LinkedIn, and I have a lot of
involves LinkedIn, and I have a lot of success sharing projects on here and
success sharing projects on here and gaining future opportunities because of
gaining future opportunities because of it. Inside your profile area, they have
it. Inside your profile area, they have a section down here at the bottom on
a section down here at the bottom on projects. And this is where you can
projects. And this is where you can showcase all your different work. It's
showcase all your different work. It's pretty easy to go through and actually
pretty easy to go through and actually add in your project. Besides that, the
add in your project. Besides that, the second option is what I also recommend
second option is what I also recommend of actually just making a post and then
of actually just making a post and then linking to that project that you've
linking to that project that you've created about this. However, there's a
created about this. However, there's a pretty key limitation with sharing
pretty key limitation with sharing projects in LinkedIn. I'm going to go
projects in LinkedIn. I'm going to go through this data science one just to
through this data science one just to show specifically. I can write about it
show specifically. I can write about it inside of here and say what I did, but
inside of here and say what I did, but then if I want to direct them or give
then if I want to direct them or give them the file of what I did, where do I
them the file of what I did, where do I do? The only thing I can do is link them
do? The only thing I can do is link them to another location. which now gets into
to another location. which now gets into this is my second option for how you
this is my second option for how you should combine this with LinkedIn to not
should combine this with LinkedIn to not only share on LinkedIn but also put all
only share on LinkedIn but also put all your work inside of here. For those that
your work inside of here. For those that are not familiar with GitHub, GitHub is
are not familiar with GitHub, GitHub is an online repository that allows you to
an online repository that allows you to keep track of all your different
keep track of all your different projects that you're working on. I go
projects that you're working on. I go through and actually like you noticed
through and actually like you noticed before I've shared all my courses here
before I've shared all my courses here because I consider it my work and it
because I consider it my work and it makes it super simple for somebody to
makes it super simple for somebody to come in and actually view it. Anyway,
come in and actually view it. Anyway, let's get into what we're going to be
let's get into what we're going to be building for this. Specifically, we're
building for this. Specifically, we're going to be setting up what's called a
going to be setting up what's called a readme file, which that's what this is
readme file, which that's what this is below here. And this is going to
below here. And this is going to document on GitHub all of the different
document on GitHub all of the different work we did in creating this dashboard.
work we did in creating this dashboard. We're include all the different skills
We're include all the different skills we showcased while building this. And
we showcased while building this. And then we're going to break down each of
then we're going to break down each of those pages that we've created while
those pages that we've created while building this. Now, this, like I
building this. Now, this, like I mentioned, is the readme, but then I can
mentioned, is the readme, but then I can also store this PowerBI file, which is
also store this PowerBI file, which is right there. And so, if a user wanted to
right there. And so, if a user wanted to access it, all they got to do is just
access it, all they got to do is just download it. And they just do this by
download it. And they just do this by clicking on the file and then going down
clicking on the file and then going down to download. And you may be like, Luke,
to download. And you may be like, Luke, what about the PowerBI service? How
what about the PowerBI service? How could you integrate that with this?
could you integrate that with this? Well, I actually integrated this with
Well, I actually integrated this with this readme if you have the option for
this readme if you have the option for this. Anyway, I include a link inside of
this. Anyway, I include a link inside of here. It says, "Hey, view the
here. It says, "Hey, view the interactive dashboard here on the
interactive dashboard here on the PowerBI service." I click on it and this
PowerBI service." I click on it and this navigates me to the online version of
navigates me to the online version of our dashboard and people can go through
our dashboard and people can go through and actually interact with it to see all
and actually interact with it to see all that we built and get some use out of
that we built and get some use out of it. Now, I feel a majority of you are
it. Now, I feel a majority of you are not going to be actually using the
not going to be actually using the PowerBI service because it costs $14 a
PowerBI service because it costs $14 a month. And frankly, I feel that's
month. And frankly, I feel that's overpriced just to host a project. So,
overpriced just to host a project. So, that'll be a completely optional
that'll be a completely optional statement that you'll be able to include
statement that you'll be able to include if you want to or not in your GitHub
if you want to or not in your GitHub repo. So, for the remainder of this
repo. So, for the remainder of this video, we're going to be going through
video, we're going to be going through these three major steps in order to get
these three major steps in order to get our work into a readme and then onto
our work into a readme and then onto GitHub and then share on LinkedIn. Let's
GitHub and then share on LinkedIn. Let's walk through it real quick. In the first
walk through it real quick. In the first portion, we're going to install all the
portion, we're going to install all the required tools. Don't worry, they're
required tools. Don't worry, they're completely free. Specifically, they
completely free. Specifically, they consist of a tool of Git and also VS
consist of a tool of Git and also VS Code. Git works in the background and is
Code. Git works in the background and is basically going to track all of our
basically going to track all of our different changes and allow us to
different changes and allow us to monitor our work. And then VS Code is
monitor our work. And then VS Code is what's working on the front end to allow
what's working on the front end to allow us to create that readme, organize our
us to create that readme, organize our project files, and then send that up to
project files, and then send that up to GitHub. Because of that, we're going to
GitHub. Because of that, we're going to need a GitHub account, which we're going
need a GitHub account, which we're going to do during this portion. For the
to do during this portion. For the second part, we're going to prepare the
second part, we're going to prepare the project. We're going to create that
project. We're going to create that readme that I showed you on GitHub and
readme that I showed you on GitHub and then set up the file and folder se uh
then set up the file and folder se uh structure correctly to where we can then
structure correctly to where we can then upload it. Which takes us to our third
upload it. Which takes us to our third point of sharing our work. We're going
point of sharing our work. We're going to put it onto GitHub and then link it
to put it onto GitHub and then link it on our LinkedIn and also make a post.
on our LinkedIn and also make a post. Like I mentioned before, this isn't of
Like I mentioned before, this isn't of interest to you, feel free to skip to
interest to you, feel free to skip to the next video.
the next video. The first thing we need to do is get Git
The first thing we need to do is get Git installed. Now, Git is a free and
installed. Now, Git is a free and open-source distributed version control
open-source distributed version control system designed to handle everything
system designed to handle everything from small to very large projects. It's
from small to very large projects. It's by far the most popular tool used for
by far the most popular tool used for basically tracking changes with files
basically tracking changes with files and allowing large teams to collaborate
and allowing large teams to collaborate together. to break it down more simply
together. to break it down more simply on what it actually is or what's
on what it actually is or what's happening there. Here I am inside of my
happening there. Here I am inside of my folder or what we'll know as my repo
folder or what we'll know as my repo repository for PowerBI. Anyway, there's
repository for PowerBI. Anyway, there's some hidden files in here. I'm on a Mac.
some hidden files in here. I'm on a Mac. I'm going to press command shift period
I'm going to press command shift period and I can unhide these files. Anyway, I
and I can unhide these files. Anyway, I have agit file and a.get ignore. Anyway,
have agit file and a.get ignore. Anyway, the file is the more important one here.
the file is the more important one here. Basically, this is the file that's being
Basically, this is the file that's being maintained to keep track of all the
maintained to keep track of all the different tri uh different changes
different tri uh different changes inside of this project. Because I am
inside of this project. Because I am using git to manage this project, it
using git to manage this project, it then allows me to then host this project
then allows me to then host this project online, specifically on GitHub. GitHub
online, specifically on GitHub. GitHub being an online repository for those
being an online repository for those that are using Git. They can send things
that are using Git. They can send things to this what we call a remote repository
to this what we call a remote repository to keep your projects here. Anyway, if I
to keep your projects here. Anyway, if I didn't have Git locally on my computer
didn't have Git locally on my computer whenever I build these projects, then I
whenever I build these projects, then I can't use GitHub. So, this allows me to
can't use GitHub. So, this allows me to use GitHub. Anyway, back to the page
use GitHub. Anyway, back to the page where we need to download Git. You can
where we need to download Git. You can just navigate to the link below and
just navigate to the link below and we're going to go into downloads. You're
we're going to go into downloads. You're most likely on a Windows. Select that
most likely on a Windows. Select that and we'll start to click here to
and we'll start to click here to download using the ARM 64 version. for
download using the ARM 64 version. for you. It should probably recommend what
you. It should probably recommend what type of computer you have. You may have
type of computer you have. You may have an x64. It'll recommend up at the top.
an x64. It'll recommend up at the top. Click that one. Once download's
Click that one. Once download's complete, launch it, allow it to access
complete, launch it, allow it to access your device. We're going to go through
your device. We're going to go through the installation, and just leave
the installation, and just leave everything set to the default. There are
everything set to the default. There are about 10ish items that I selected. Okay.
about 10ish items that I selected. Okay. And now I'm installing. Once it's
And now I'm installing. Once it's complete, I'm going toclick this and
complete, I'm going toclick this and then just go in finish. Git is now
then just go in finish. Git is now installed. The next step is getting VS
installed. The next step is getting VS Code. Now, this tool of VS Code is a
Code. Now, this tool of VS Code is a text editor and it's pretty simple. I
text editor and it's pretty simple. I just want to demo it before we actually
just want to demo it before we actually go and install it. We're allowed to see
go and install it. We're allowed to see all the different files for a project.
all the different files for a project. So, in this case, this is my PowerBI
So, in this case, this is my PowerBI file and we're downloading this and
file and we're downloading this and using this for two main reasons. First
using this for two main reasons. First of all is because we'll be able to
of all is because we'll be able to create a readme inside of here. And this
create a readme inside of here. And this readme uses a special markup language
readme uses a special markup language which I can view what this markup
which I can view what this markup language looks like or what it's going
language looks like or what it's going to look like on the internet right next
to look like on the internet right next to it. If you recall, this looks very
to it. If you recall, this looks very similar to what's on GitHub. The other
similar to what's on GitHub. The other main reason why we're using this is
main reason why we're using this is because this allows us to interact and
because this allows us to interact and push this up to GitHub using Git behind
push this up to GitHub using Git behind the scenes. So this is a great tool
the scenes. So this is a great tool especially I like using this with things
especially I like using this with things like Python and SQL. Anyway, how are we
like Python and SQL. Anyway, how are we going to install it? Just go to the
going to install it? Just go to the Microsoft Store, search for VS Code, and
Microsoft Store, search for VS Code, and it should be the first one. Not this
it should be the first one. Not this one. That's the insiders, but this one
one. That's the insiders, but this one right here. Once it's installed, you can
right here. Once it's installed, you can just open it right up. They have a
just open it right up. They have a getting started screen right here. We're
getting started screen right here. We're going to skip this for the time being.
going to skip this for the time being. I'm just going to close out of it. The
I'm just going to close out of it. The last portion to do in setup is setting
last portion to do in setup is setting up our GitHub account. For this one,
up our GitHub account. For this one, pretty simple. All you have to do is
pretty simple. All you have to do is just go enter your email and sign up for
just go enter your email and sign up for GitHub. Once logged in, you should be
GitHub. Once logged in, you should be directed to your profile. If not, click
directed to your profile. If not, click your icon in the upper right hand corner
your icon in the upper right hand corner and navigate to your profile. Anyway,
and navigate to your profile. Anyway, with this, I would go forward and
with this, I would go forward and actually set up well, setting up your
actually set up well, setting up your profile, specifically adding a profile
profile, specifically adding a profile picture, and then any other links or
picture, and then any other links or information about yourself inside of
information about yourself inside of here. Over here on the right are my
here. Over here on the right are my pinned repositories, and you'll be able
pinned repositories, and you'll be able to add this later on whenever we add our
to add this later on whenever we add our project.
Now that we have everything needed installed, we're going to now jump into
installed, we're going to now jump into preparing our project. We're going to do
preparing our project. We're going to do two major steps. First is just setting
two major steps. First is just setting up our project and having our folder
up our project and having our folder where we need it access accessed inside
where we need it access accessed inside of VS Code. And the second step, which
of VS Code. And the second step, which is probably the longer step, is actually
is probably the longer step, is actually creating our readme. First thing we need
creating our readme. First thing we need to do in getting our project folder all
to do in getting our project folder all together is well getting our PowerBI
together is well getting our PowerBI file in order. Specifically, we've been
file in order. Specifically, we've been working within this entire folder or
working within this entire folder or this entire file that has all of our
this entire file that has all of our work from everything in chapter 2. I
work from everything in chapter 2. I only want to have the dashboard page and
only want to have the dashboard page and the drill through page in there. So, how
the drill through page in there. So, how are we going to do this? Well, first I'm
are we going to do this? Well, first I'm going to save this with the appropriate
going to save this with the appropriate title so that way I don't lose any work
title so that way I don't lose any work just in case. I'm going to save it as a
just in case. I'm going to save it as a new file. So, I'm going to save it with
new file. So, I'm going to save it with the name data jobs dashboard and save it
the name data jobs dashboard and save it to a name known location. I'm saving it
to a name known location. I'm saving it to the desktop for me. Now that I can
to the desktop for me. Now that I can see it is saved, I can then go through
see it is saved, I can then go through and get rid of all the different other
and get rid of all the different other pages. Also, I added these home icons on
pages. Also, I added these home icons on here. I don't think we you did, but if
here. I don't think we you did, but if you did happen to, I'd go ahead and
you did happen to, I'd go ahead and remove them cuz it's not going to take
remove them cuz it's not going to take you anywhere. With the dashboard or the
you anywhere. With the dashboard or the homepage selected, that's very important
homepage selected, that's very important you do this. Now, go ahead and save this
you do this. Now, go ahead and save this because whenever somebody opens this
because whenever somebody opens this file, it's going to be navigated to
file, it's going to be navigated to whatever page you have saved last. At
whatever page you have saved last. At this time, I'd also recommend going
this time, I'd also recommend going through and publishing to the PowerBI
through and publishing to the PowerBI service if you have that set up. Once
service if you have that set up. Once that's done, I'm going to go ahead and
that's done, I'm going to go ahead and close out of it. So, let's go ahead and
close out of it. So, let's go ahead and open the folder for our project or for
open the folder for our project or for the folder that we're going to be using
the folder that we're going to be using for this. In this, I'm going to go ahead
for this. In this, I'm going to go ahead and select file and then new window.
and select file and then new window. Whenever I do this, I have this start
Whenever I do this, I have this start open and it says, hey, do you want to
open and it says, hey, do you want to open a folder? Yes, I do. Specifically,
open a folder? Yes, I do. Specifically, we need to open our project folder,
we need to open our project folder, which we haven't created yet. So, I'm
which we haven't created yet. So, I'm going to click on desktop because that's
going to click on desktop because that's where I want it. Going to create a new
where I want it. Going to create a new folder. And then I'm going to name it
folder. And then I'm going to name it what I want the name of this project to
what I want the name of this project to be called, and I'm going to call it
be called, and I'm going to call it simple like PowerBI dashboard. It's
simple like PowerBI dashboard. It's going to select that and select folder.
going to select that and select folder. It's ask if I trust the author of this.
It's ask if I trust the author of this. The author's me. I don't really trust
The author's me. I don't really trust myself, but I'm going to click yes
myself, but I'm going to click yes anyway. Now, right now over here on the
anyway. Now, right now over here on the left hand side, this is the file
left hand side, this is the file explorer. And right now, there's no
explorer. And right now, there's no files inside of it. So, first of all, we
files inside of it. So, first of all, we want our PowerBI file inside of here.
want our PowerBI file inside of here. The easiest way to get it in there is
The easiest way to get it in there is just open up File Explorer, drag that
just open up File Explorer, drag that PowerBI file that we have wherever you
PowerBI file that we have wherever you have it saved and into PowerBI
have it saved and into PowerBI dashboards. Closing this out, see that
dashboards. Closing this out, see that the PowerBI file is now there. Notice
the PowerBI file is now there. Notice you're going to have this sort of error
you're going to have this sort of error message. This file is not displayed in
message. This file is not displayed in text ed because it's either binary and
text ed because it's either binary and well, it is binary. It doesn't support
well, it is binary. It doesn't support the method to actually view it here. You
the method to actually view it here. You can't view PowerBI files in VS Code. Not
can't view PowerBI files in VS Code. Not a big deal. going to close out of this.
a big deal. going to close out of this. Now, the next thing we want to do is
Now, the next thing we want to do is create a readme. So, up here on the
create a readme. So, up here on the icons, you can create a new file, a new
icons, you can create a new file, a new folder, and whatnot. We're going to
folder, and whatnot. We're going to create a new file. For this, we want to
create a new file. For this, we want to create a markdown file called readme.
create a markdown file called readme. It's really important we name this
It's really important we name this correctly. So, read me in all caps and
correctly. So, read me in all caps and then MD. When we do that, read me opens
then MD. When we do that, read me opens up on the right hand side for us to go
up on the right hand side for us to go through and text edit it. They have this
through and text edit it. They have this popup here for basically prompting us to
popup here for basically prompting us to use GitHub Copilot. You can use that if
use GitHub Copilot. You can use that if you want or not. We're not going to try
you want or not. We're not going to try to demo it for this video. Anyway, I can
to demo it for this video. Anyway, I can type things in here like this is a test.
type things in here like this is a test. And then if we want to see what it looks
And then if we want to see what it looks like, we come up here to the right hand
like, we come up here to the right hand side and we open the preview to the
side and we open the preview to the side. I'm going to minimize the explorer
side. I'm going to minimize the explorer right here. So, we can see things like
right here. So, we can see things like this is a test. Now, how we're going to
this is a test. Now, how we're going to go through some basics now of how to
go through some basics now of how to format in Markdown. Well, if you
format in Markdown. Well, if you navigate to the link below, this
navigate to the link below, this provides a cheat sheet of how you can
provides a cheat sheet of how you can use this basic syntax in order to mark
use this basic syntax in order to mark up your document. We're going to go
up your document. We're going to go through these basic items first. So,
through these basic items first. So, first thing is I want a heading. So, I'm
first thing is I want a heading. So, I'm going to put a hashtag and then followed
going to put a hashtag and then followed by what we want to put. In this case, I
by what we want to put. In this case, I put the title of our project. I could
put the title of our project. I could also do things like a heading. That was
also do things like a heading. That was a heading one. I could do a heading two
a heading one. I could do a heading two and put an introduction and then
and put an introduction and then underneath it put a couple sentences of
underneath it put a couple sentences of what we went through and actually did
what we went through and actually did here. Now, there's some things I want to
here. Now, there's some things I want to emphasize in this and so I want to bold
emphasize in this and so I want to bold them. In order to do that, I'm going to
them. In order to do that, I'm going to put two asterisk
put two asterisk asterises around where I want it to bold
asterises around where I want it to bold and luckily it makes it nice and
and luckily it makes it nice and highlighting it here inside the markdown
highlighting it here inside the markdown file, but then you can also see it in
file, but then you can also see it in the preview. I could also use something
the preview. I could also use something like a single asterisk to make things
like a single asterisk to make things into an italics. Now, let's move on to
into an italics. Now, let's move on to some other items. I'm going to go into
some other items. I'm going to go into what skills we showcased with this. And
what skills we showcased with this. And in this, I want to use bullet points.
in this, I want to use bullet points. So, what I can do is use a dash and then
So, what I can do is use a dash and then space. And as you can see, it made into
space. And as you can see, it made into a bullet point and then list the skill.
a bullet point and then list the skill. In this case, I put data transformation
In this case, I put data transformation ETL with Power Query and then put a
ETL with Power Query and then put a little synopsis about it. I'm going to
little synopsis about it. I'm going to go ahead and add some other skills as
go ahead and add some other skills as well. Feel free to choose which ones you
well. Feel free to choose which ones you want to highlight, but specifically I
want to highlight, but specifically I have implicit measures, core charts,
have implicit measures, core charts, geospatial analysis, KPIs, and dashboard
geospatial analysis, KPIs, and dashboard design. Also go over some interactive
design. Also go over some interactive reporting, how we use slicers, butings,
reporting, how we use slicers, butings, and drill through and whatnot. Anyway,
and drill through and whatnot. Anyway, whatever we want to highlight, put it
whatever we want to highlight, put it there. Now, if you remember from my repo
there. Now, if you remember from my repo on my readme, we had an image up at the
on my readme, we had an image up at the top. How the heck do we go about putting
top. How the heck do we go about putting an image in here? Well, navigating into
an image in here? Well, navigating into that PowerBI file, we're going to go
that PowerBI file, we're going to go ahead and use a tool called snip that's
ahead and use a tool called snip that's automatically on your Windows computer.
automatically on your Windows computer. For this, as it says, you need to press
For this, as it says, you need to press the Windows logo key plus shift plus S.
the Windows logo key plus shift plus S. So, I'm going to do that right here and
So, I'm going to do that right here and snapshot that bad boy. I selected markup
snapshot that bad boy. I selected markup and share. So, I want to go in and
and share. So, I want to go in and actually save it somewhere. So, I'm
actually save it somewhere. So, I'm going to navigate back to that PowerBI
going to navigate back to that PowerBI dashboards file folder that we have, and
dashboards file folder that we have, and I'm going to create a new folder in here
I'm going to create a new folder in here called images because I want to keep all
called images because I want to keep all my images in one spot. Not that I'm all
my images in one spot. Not that I'm all over the place. Anyway, inside of here,
over the place. Anyway, inside of here, I'm just going to call something like
I'm just going to call something like project one, page one. Then, I'm going
project one, page one. Then, I'm going to repeat this again for the second
to repeat this again for the second page. Saving it as project one, page
page. Saving it as project one, page two. Save it. So, now let's put this
two. Save it. So, now let's put this image inside of our readme. In our
image inside of our readme. In our little cheat sheet here, we can see that
little cheat sheet here, we can see that in order to insert an image, we need to
in order to insert an image, we need to use this syntax right here. So, I'm
use this syntax right here. So, I'm going to go ahead and just copy this and
going to go ahead and just copy this and then paste it right above the title.
then paste it right above the title. Notice here it's got this broken image
Notice here it's got this broken image because we haven't connected the image
because we haven't connected the image yet. I'm going to call this dashboard
yet. I'm going to call this dashboard page one. And then inside of parentheses
page one. And then inside of parentheses here, that's where we want to go to the
here, that's where we want to go to the location of the file. I'm going to hit
location of the file. I'm going to hit forward slash. And then this is going to
forward slash. And then this is going to pop up show me all the different files
pop up show me all the different files here in this repo. Remember if I open up
here in this repo. Remember if I open up the explorer I can also see them here.
the explorer I can also see them here. So let me demo that again. Whenever I
So let me demo that again. Whenever I hit this I get data jobs dashboard which
hit this I get data jobs dashboard which is right here. Images folder and read
is right here. Images folder and read me. Let's go into images. And then from
me. Let's go into images. And then from there I can do backslash again and
there I can do backslash again and insert in what file I want. I want this
insert in what file I want. I want this project one page one png. And then put
project one page one png. And then put that close parenthesis. And bam. Now
that close parenthesis. And bam. Now it's appearing right here on our
it's appearing right here on our readman. We'll close this out. Make this
readman. We'll close this out. Make this a little more readable. Now, below these
a little more readable. Now, below these skills showcased, I'd like to also go
skills showcased, I'd like to also go through and break down which uh contents
through and break down which uh contents or what each one of these pages
or what each one of these pages contains. So, I'm going to create a
contains. So, I'm going to create a heading two for dashboard overview and
heading two for dashboard overview and then do a heading three to de uh to go
then do a heading three to de uh to go over page one highle market view. For
over page one highle market view. For this, I'm just going to copy this image
this, I'm just going to copy this image that we have above and put it in right
that we have above and put it in right underneath this. Now, with that, now
underneath this. Now, with that, now that it's in there, I'm just going to
that it's in there, I'm just going to give a short little description under
give a short little description under this, maybe one to two sentences of what
this, maybe one to two sentences of what we're doing in this page one of our
we're doing in this page one of our dashboard. And then right underneath
dashboard. And then right underneath this, I'm going to do the same thing for
this, I'm going to do the same thing for page number two. And then finally,
page number two. And then finally, underneath it, I'm going to wrap it up
underneath it, I'm going to wrap it up with a conclusion. What are my lessons
with a conclusion. What are my lessons learned? What did I get out of this
learned? What did I get out of this project? All right. Bam. This project
project? All right. Bam. This project readme is done. One quick note, if you
readme is done. One quick note, if you did share this on the PowerBI service, I
did share this on the PowerBI service, I would go ahead and add that link in
would go ahead and add that link in right here, right below the picture, the
right here, right below the picture, the first picture. For links, what we're
first picture. For links, what we're going to do is we're going to put every
going to do is we're going to put every all the words that we want in the link
all the words that we want in the link in brackets and then in parentheses,
in brackets and then in parentheses, we're going to put the hyperlink to
we're going to put the hyperlink to where the dashboard is. It's similar to
where the dashboard is. It's similar to pictures, but it doesn't have that
pictures, but it doesn't have that exclamation point in the front of it.
exclamation point in the front of it. Anyway, I created a shorter link. And so
Anyway, I created a shorter link. And so now I whenever I go to click on this, it
now I whenever I go to click on this, it will navigate me into my web browser
will navigate me into my web browser which connects me directly to the
which connects me directly to the dashboards itself. Pretty neat.
dashboards itself. Pretty neat. All right, so we've set up our entire
All right, so we've set up our entire project folder and created that readme.
project folder and created that readme. Next thing we do, smooth sailing, we
Next thing we do, smooth sailing, we need to upload to GitHub and then share
need to upload to GitHub and then share on LinkedIn. So inside of VS Code, I'm
on LinkedIn. So inside of VS Code, I'm going to close out this preview, but I'm
going to close out this preview, but I'm going to go ahead and save this by
going to go ahead and save this by pressing Ctrl S. You can also just go up
pressing Ctrl S. You can also just go up into file and select save as well. And
into file and select save as well. And I'm going to close out of this. Open
I'm going to close out of this. Open back up that file explorer. Okay, so
back up that file explorer. Okay, so this is our folder structure right now,
this is our folder structure right now, right? We have a PowerBI file, the
right? We have a PowerBI file, the readme, and then our images in here. In
readme, and then our images in here. In project two, we're going to modify this
project two, we're going to modify this structure and also upload the same thing
structure and also upload the same thing into GitHub. But for now, being this is
into GitHub. But for now, being this is going to be perfectly fine. So I'm going
going to be perfectly fine. So I'm going to move on down here and go into source
to move on down here and go into source control. And what's going to happen with
control. And what's going to happen with this now is we have two options to
this now is we have two options to either initialize the repository and
either initialize the repository and that's basically setting up git to track
that's basically setting up git to track those changes within it. And then the
those changes within it. And then the second option is publish to GitHub which
second option is publish to GitHub which is basically initializing the repository
is basically initializing the repository and then publishing to GitHub. So it
and then publishing to GitHub. So it takes the next step of publishing to
takes the next step of publishing to GitHub. We want to do this second option
GitHub. We want to do this second option to just but because that's what our end
to just but because that's what our end goal is. So I'm going to go ahead and
goal is. So I'm going to go ahead and select publish to GitHub. and it says,
select publish to GitHub. and it says, "Hey, we want to sign into GitHub
"Hey, we want to sign into GitHub because right now VS Code is not linked
because right now VS Code is not linked to GitHub." Go ahead and authorize it.
to GitHub." Go ahead and authorize it. And I'm going to enable to always allow
And I'm going to enable to always allow VS Code to open links of this type. Oh
VS Code to open links of this type. Oh no, I didn't mean to click cancel.
no, I didn't mean to click cancel. Oh well, it'll be fine. In here for the
Oh well, it'll be fine. In here for the name of the dashboard, I'm going to
name of the dashboard, I'm going to press enter. Actually was a big deal. I
press enter. Actually was a big deal. I need to go back and select open. Anyway,
need to go back and select open. Anyway, it's asking, do we want to publish as a
it's asking, do we want to publish as a private or public repository? We want to
private or public repository? We want to make this public. It's asking us what
make this public. It's asking us what files do we want to include in this. We
files do we want to include in this. We want to include all of these files in
want to include all of these files in here. So, I'm going to select okay. It's
here. So, I'm going to select okay. It's telling me I'm thinking because I'm in
telling me I'm thinking because I'm in working in a virtual machine with
working in a virtual machine with parallels that I need to manage my
parallels that I need to manage my unsafe repositories. You may not have
unsafe repositories. You may not have that popup, but anyway, I selected it
that popup, but anyway, I selected it and moved on. Now, we're going to be
and moved on. Now, we're going to be committing this as their changes and
committing this as their changes and then from there pushing it to GitHub.
then from there pushing it to GitHub. So, I'm just going to enter a message in
So, I'm just going to enter a message in here. I'm going to enter in something
here. I'm going to enter in something original like first commit and then
original like first commit and then click commit. There's a popup and says
click commit. There's a popup and says there are no stage changes to commit.
there are no stage changes to commit. Okay. Would you like to stage all
Okay. Would you like to stage all changes and commit them directly? For
changes and commit them directly? For this, I will have this set to always. I
this, I will have this set to always. I always want to do this. Now, you may get
always want to do this. Now, you may get this error right here. Make sure you
this error right here. Make sure you configure your username and user email
configure your username and user email in Git. This is really common. So, what
in Git. This is really common. So, what I'm going to do is I'm going to cancel
I'm going to do is I'm going to cancel out of this. And then from there, in the
out of this. And then from there, in the search menu, I'm going to go enter git.
search menu, I'm going to go enter git. and we're going to go to get bash, which
and we're going to go to get bash, which is actually an app that we installed
is actually an app that we installed when we installed git. You're going to
when we installed git. You're going to type in this get config--global
type in this get config--global user.name Luke Bruce. So, we just set
user.name Luke Bruce. So, we just set our name. We now need to set our email.
our name. We now need to set our email. So, then we're going to run get
So, then we're going to run get config--global
config--global user.mail and then in double quotes your
user.mail and then in double quotes your email and then press enter. Now, back
email and then press enter. Now, back here in VS Code, it's going to say, hey,
here in VS Code, it's going to say, hey, I want to publish the branch. and it's
I want to publish the branch. and it's going to take you through. There's a
going to take you through. There's a little bit of a issue or a flaw with VS
little bit of a issue or a flaw with VS Code. It's going to try to take you
Code. It's going to try to take you through going through and setting up the
through going through and setting up the repository again. Say, "Hey, you've set
repository again. Say, "Hey, you've set this up already. It already exists." So,
this up already. It already exists." So, we got to do a little bit more
we got to do a little bit more interaction with the terminal. In order
interaction with the terminal. In order to do this, we're going to come up to
to do this, we're going to come up to the file menu and go into terminal and
the file menu and go into terminal and select, hey, we want a new terminal. And
select, hey, we want a new terminal. And we're going to run this command, get
we're going to run this command, get remote add origin. And it's really
remote add origin. And it's really important that we have the correct link
important that we have the correct link of where your dashboard is on GitHub.
of where your dashboard is on GitHub. Specifically, it should be github.com
Specifically, it should be github.com your username and then the name of our
your username and then the name of our dashboard and then.get. Go ahead and
dashboard and then.get. Go ahead and click enter. So, I did some changes up
click enter. So, I did some changes up here. Let's try this again. I have a
here. Let's try this again. I have a popup here to I don't know why it's
popup here to I don't know why it's super small like this. I got a popup
super small like this. I got a popup here and it says sign in with your
here and it says sign in with your computer. It asks if I want to authorize
computer. It asks if I want to authorize the Git ecosystem. I in fact do. And it
the Git ecosystem. I in fact do. And it looks like everything from VS Code is um
looks like everything from VS Code is um sent up there. So now inside of GitHub I
sent up there. So now inside of GitHub I can go here on the right hand side if I
can go here on the right hand side if I go to your repositories I can see that
go to your repositories I can see that my PowerBI dashboard is there that
my PowerBI dashboard is there that folder and it has everything all the
folder and it has everything all the folders and files that we had along with
folders and files that we had along with our readme that we created with all the
our readme that we created with all the different information in it. It's all
different information in it. It's all there. All right. There's only two steps
there. All right. There's only two steps left and they're both on LinkedIn. The
left and they're both on LinkedIn. The first is navigating down to your project
first is navigating down to your project section and adding in this new project.
section and adding in this new project. In here, I might give it a name, a short
In here, I might give it a name, a short description. I'm going to list some of
description. I'm going to list some of the key skills. You can list up to five,
the key skills. You can list up to five, but make sure you're calling out PowerBI
but make sure you're calling out PowerBI specifically. Also call it gout git and
specifically. Also call it gout git and GitHub. Adding media is probably the
GitHub. Adding media is probably the most important part. And that's for we
most important part. And that's for we want to include a link to our GitHub
want to include a link to our GitHub repo right here. Once that media is
repo right here. Once that media is added, just select a start and end date.
added, just select a start and end date. And then from there, go ahead click
And then from there, go ahead click save. Last main portion is now making a
save. Last main portion is now making a post in it. Feel free to call out myself
post in it. Feel free to call out myself and Kelly. I love checking out all your
and Kelly. I love checking out all your different projects. And then also share
different projects. And then also share that link to it. I included also a
that link to it. I included also a picture to make it a little more
picture to make it a little more interactive. And go ahead and post it.
interactive. And go ahead and post it. All right. So, you've made it this far
All right. So, you've made it this far in this video of sharing the dashboard.
in this video of sharing the dashboard. Congratulations. Sharing it, especially
Congratulations. Sharing it, especially GitHub, especially the first time, is
GitHub, especially the first time, is intimidating, but I promise you, the
intimidating, but I promise you, the more and more familiar you get with it,
more and more familiar you get with it, the easier it becomes. And it's my
the easier it becomes. And it's my recommended choice, this method of
recommended choice, this method of sharing that I use for sharing any type
sharing that I use for sharing any type of work, whether it's PowerBI, Python,
of work, whether it's PowerBI, Python, SQL, or whatnot. All right, in the next
SQL, or whatnot. All right, in the next video, we're going to be jumping
video, we're going to be jumping straight into more of an advanced
straight into more of an advanced section, jumping into Power Query, so we
section, jumping into Power Query, so we can see how to clean up some data. With
can see how to clean up some data. With that, I'll see you there.
All right, welcome to the second half of this course and we're about to crank
this course and we're about to crank things up a notch. Specifically, we have
things up a notch. Specifically, we have two chapters left. This one on Power
two chapters left. This one on Power Query and the next one on DAX. Both of
Query and the next one on DAX. Both of these are going to supercharge your
these are going to supercharge your powers and PowerBI in order to make more
powers and PowerBI in order to make more effective visualizations. Anyway, into
effective visualizations. Anyway, into this chapter. This one's going to be
this chapter. This one's going to be focused on Power Query. Power Query is a
focused on Power Query. Power Query is a tool used for ETL or extract, transform,
tool used for ETL or extract, transform, and load. You hear data engineers talk
and load. You hear data engineers talk about this all the time. Let's demo a
about this all the time. Let's demo a use case real quick. So, back to my old
use case real quick. So, back to my old days working as a data analyst. Every
days working as a data analyst. Every month, I'd get a new report similar to
month, I'd get a new report similar to this where in this case, that's the job
this where in this case, that's the job postings, but this is for all the job
postings, but this is for all the job postings in January. So, like any good
postings in January. So, like any good employee, I then take that Excel sheet
employee, I then take that Excel sheet for my boss and put it into a PowerBI
for my boss and put it into a PowerBI dashboard. this case, I have a job count
dashboard. this case, I have a job count and then also the jobs overtime in
and then also the jobs overtime in January. But then we get into our next
January. But then we get into our next month and February rolls around and I
month and February rolls around and I get this new Excel spreadsheet that we
get this new Excel spreadsheet that we can tell by job posted date has the jobs
can tell by job posted date has the jobs from February 2024. What the heck am I
from February 2024. What the heck am I supposed to do now? Well, I know what a
supposed to do now? Well, I know what a lot of you done before because I've done
lot of you done before because I've done it too. I've had to collect all this
it too. I've had to collect all this different data and specifically copying
different data and specifically copying it using control C and then navigating
it using control C and then navigating into my January file, scrolling all the
into my January file, scrolling all the way to the bottom and then putting this
way to the bottom and then putting this data in here inside of here, saving it,
data in here inside of here, saving it, and then going back into my PowerBI file
and then going back into my PowerBI file and clicking refresh now that that
and clicking refresh now that that January file is or that former January
January file is or that former January file is now January February. So I can
file is now January February. So I can get this new data in. And then these
get this new data in. And then these jobs are now updated to include not only
jobs are now updated to include not only January but also February. Also got to
January but also February. Also got to update this title. But our data is now
update this title. But our data is now updated. Mind you, I have to do that
updated. Mind you, I have to do that copy from that other file to the new
copy from that other file to the new file. If only there was an easier
file. If only there was an easier solution. Well, with Power Query, there
solution. Well, with Power Query, there is. All I have to do is put a folder
is. All I have to do is put a folder with the Excel files I need. So in this
with the Excel files I need. So in this case, I have the January and February.
case, I have the January and February. Let's now add in March. So I'll paste it
Let's now add in March. So I'll paste it in. And now we have three months worth
in. And now we have three months worth of data. Whenever I go back to PowerBI,
of data. Whenever I go back to PowerBI, click refresh. In this case, I've set it
click refresh. In this case, I've set it up to now pull from this folder. You
up to now pull from this folder. You didn't see this. I'll show this in the
didn't see this. I'll show this in the video. And now these files are updated
video. And now these files are updated for actually just go up to make this a
for actually just go up to make this a little bit easier. They're updated for
little bit easier. They're updated for January, February, and also March. Now,
January, February, and also March. Now, you may be like, Luke, you still had to
you may be like, Luke, you still had to click that refresh button. Well,
click that refresh button. Well, actually, if you put it into something
actually, if you put it into something like the PowerBI service using publish,
like the PowerBI service using publish, you can schedule automated refreshes.
you can schedule automated refreshes. But we're getting ahead of oursel.
So, just make sure we're on the same page. What is Power Query? Like I said,
page. What is Power Query? Like I said, it's an ETL tool in order to form
it's an ETL tool in order to form extraction, transformation, and loading.
extraction, transformation, and loading. In that previous example, we extracted
In that previous example, we extracted data out of a folder. We transformed it
data out of a folder. We transformed it by putting it all into a single table
by putting it all into a single table and then loaded it here into power query
and then loaded it here into power query or into PowerBI so we could visualize
or into PowerBI so we could visualize it. ETL you access power query inside of
it. ETL you access power query inside of PowerBI
PowerBI underneath the home tab. Basically this
underneath the home tab. Basically this entire section right here on data and
entire section right here on data and also queries. This is Power Query. Fun
also queries. This is Power Query. Fun fact, if you're inside of Excel, you
fact, if you're inside of Excel, you would just navigate to the data tab. And
would just navigate to the data tab. And there, like right here on get and
there, like right here on get and transform data and queries and
transform data and queries and connections. This is the portion that
connections. This is the portion that deals with Power Query. Everything that
deals with Power Query. Everything that you're going to learn from me today in
you're going to learn from me today in using Power Query inside of PowerBI is
using Power Query inside of PowerBI is going to be able to replicated and used
going to be able to replicated and used inside of Excel. So, this chapter on
inside of Excel. So, this chapter on Power Query is going to be broken up
Power Query is going to be broken up into six different lessons. In this
into six different lessons. In this lesson, we're going to have an intro, do
lesson, we're going to have an intro, do some basic examples, and then next one,
some basic examples, and then next one, we're going to get into using basically
we're going to get into using basically another guey called the Power Query
another guey called the Power Query Editor in order to edit our
Editor in order to edit our transformations. In the third lesson,
transformations. In the third lesson, we're going to be moving into actually
we're going to be moving into actually importing in the data we're going to be
importing in the data we're going to be using for the final project. And then
using for the final project. And then from there, with the three remaining
from there, with the three remaining lessons, we're going to get into some
lessons, we're going to get into some more advanced techniques and using
more advanced techniques and using things like the M language, append, and
things like the M language, append, and merge, and whatnot. Now, regarding the
merge, and whatnot. Now, regarding the PowerBI files for this chapter, things
PowerBI files for this chapter, things are going to be a little bit different
are going to be a little bit different from what we did previously. In this,
from what we did previously. In this, we're going to have a file for each
we're going to have a file for each lesson. These files are going to be what
lesson. These files are going to be what is done upon completion of a lesson. So,
is done upon completion of a lesson. So, in our case, 3.1 Power Query Intro. This
in our case, 3.1 Power Query Intro. This is the completed file at the end of this
is the completed file at the end of this video.
and using those files. It's actually a great segue into getting into how to use
great segue into getting into how to use Power Query inside the home ribbon. Now,
Power Query inside the home ribbon. Now, if you were to open up this Power Query
if you were to open up this Power Query intro file and then were to hit
intro file and then were to hit something like refresh in order to
something like refresh in order to connect to all these different data
connect to all these different data sources that we are going to do and try
sources that we are going to do and try to load them in, you're going to get a
to load them in, you're going to get a few errors. Specifically with our
few errors. Specifically with our monthly files, these are located on my
monthly files, these are located on my local machine. So the path for these is
local machine. So the path for these is in power query is directing them to my
in power query is directing them to my machine. You need to update them from
machine. You need to update them from where they are for you. So I'm going to
where they are for you. So I'm going to do is close this. Go here underneath the
do is close this. Go here underneath the queries under transform data into data
queries under transform data into data source settings. In our case, you're
source settings. In our case, you're going to look for the folder icon, in
going to look for the folder icon, in this case the Z desktop monthly files,
this case the Z desktop monthly files, and you're going to go to change source.
and you're going to go to change source. And then from there, you're going to go
And then from there, you're going to go to browse and you'll locate to the area
to browse and you'll locate to the area that you have those monthly files in.
that you have those monthly files in. Click okay and okay and then close. And
Click okay and okay and then close. And then upon refreshing this, the query
then upon refreshing this, the query should load with no issues. And bam,
should load with no issues. And bam, there we have it. Anyway, so this is a
there we have it. Anyway, so this is a completed file. Let's get out of this
completed file. Let's get out of this and get into a blank PowerBI file to get
and get into a blank PowerBI file to get through this lesson. So moving on into
through this lesson. So moving on into exploring this, the first thing to
exploring this, the first thing to understand is we have an option to get
understand is we have an option to get data. And this gets data from a
data. And this gets data from a multitude of different sources. As we've
multitude of different sources. As we've saw previously, I prefer using this more
saw previously, I prefer using this more option anytime I'm trying to look for
option anytime I'm trying to look for things. There's some major types that we
things. There's some major types that we can look at. One is file things like
can look at. One is file things like Excel, text files, PDFs, whatnot. The
Excel, text files, PDFs, whatnot. The next are databases, which we're going to
next are databases, which we're going to eventually get to demoing for this. And
eventually get to demoing for this. And databases are by far, especially in the
databases are by far, especially in the business world, are the source that I'm
business world, are the source that I'm going to be using to get data primarily
going to be using to get data primarily behind files themselves, like Excel
behind files themselves, like Excel files. Now, beyond file and databases,
files. Now, beyond file and databases, there's options that are specific to the
there's options that are specific to the Microsoft platform that if your
Microsoft platform that if your company's invested billions or millions
company's invested billions or millions of dollars into this, they probably have
of dollars into this, they probably have access to these, such as Azure as well.
access to these, such as Azure as well. And the only other other one we'll call
And the only other other one we'll call out is other, specifically other because
out is other, specifically other because we're going to be able to import data
we're going to be able to import data from things like a web page or you can
from things like a web page or you can even do things like R script or Python
even do things like R script or Python script. Now, navigating back now that
script. Now, navigating back now that we've seen all that, you can see that
we've seen all that, you can see that these three options right here are
these three options right here are basically just quick actions from the
basically just quick actions from the get data. So, I don't find myself using
get data. So, I don't find myself using unless I'm going directly to like an
unless I'm going directly to like an Excel workbook. We've seen previously
Excel workbook. We've seen previously also how we can just enter data in and
also how we can just enter data in and create our own table. That's done
create our own table. That's done through Power Query. And then once again
through Power Query. And then once again data versse is another source or recent
data versse is another source or recent sources itself you can connect right to.
sources itself you can connect right to. Now moving over to this query section
Now moving over to this query section under transform data. We've explored
under transform data. We've explored data source settings. But then there's
data source settings. But then there's transform data and this is how we're
transform data and this is how we're going to get to the power query editor.
going to get to the power query editor. We're not going to touch this editor in
We're not going to touch this editor in this first lesson. We're going to keep
this first lesson. We're going to keep it simple and just load data using the
it simple and just load data using the most simple method to get into PowerBI
most simple method to get into PowerBI without getting to the editor. The last
without getting to the editor. The last two things on here that are grayed out
two things on here that are grayed out are edit uh parameters and also edit
are edit uh parameters and also edit variables. Both of these are outside of
variables. Both of these are outside of the scope of this course. Editing
the scope of this course. Editing parameters and variables are more
parameters and variables are more advanced techniques and I don't think
advanced techniques and I don't think that they're necessarily necessary for
that they're necessarily necessary for the basics. So, we're not going to be
the basics. So, we're not going to be covering it. And the last button is
covering it. And the last button is refresh, which you've seen me demo just
refresh, which you've seen me demo just recently of getting those monthly files
recently of getting those monthly files updated. But that's how we update any
updated. But that's how we update any type of query. is clicking refresh.
All right, enough of the theory. Let's actually get into some examples
actually get into some examples demonstrating power query. First one is
demonstrating power query. First one is this. Now, let's say I want to do an
this. Now, let's say I want to do an analysis to understand how things like
analysis to understand how things like GDP, gross domestic product compares to
GDP, gross domestic product compares to or how it has an impact on maybe
or how it has an impact on maybe salaries in different countries. And so
salaries in different countries. And so what I can do is I went to Bing here. I
what I can do is I went to Bing here. I uh binged if you will countries by GDP
uh binged if you will countries by GDP by sector and this first result of
by sector and this first result of Wikipedia popup. Anyway, this Wikipedia
Wikipedia popup. Anyway, this Wikipedia page includes tables in it with in this
page includes tables in it with in this case it's the nominal GDP and then also
case it's the nominal GDP and then also this real GDP. Anyway, this data is in
this real GDP. Anyway, this data is in here in a table. Previously, I know
here in a table. Previously, I know you've probably done this before. You
you've probably done this before. You probably come in here and tried to
probably come in here and tried to select it and then try to copy it. Well,
select it and then try to copy it. Well, instead power query simplifies this. I
instead power query simplifies this. I can just copy this address right here.
can just copy this address right here. Pressing C and then navigating to get
Pressing C and then navigating to get data and we want to get this from this
data and we want to get this from this web source right here from a web page.
web source right here from a web page. We'll keep it in the basic. All we have
We'll keep it in the basic. All we have to do is just paste in that URL. Click
to do is just paste in that URL. Click okay. And what's really neat now is it
okay. And what's really neat now is it shows me all the different tables within
shows me all the different tables within here. I can even select like table two,
here. I can even select like table two, which is the one we're going to get.
which is the one we're going to get. Anyway, it's really important that you
Anyway, it's really important that you go through and select which table you
go through and select which table you actually want because a lot of these
actually want because a lot of these tables are not really useful. Table 2 is
tables are not really useful. Table 2 is the most useful for us. I'm going to
the most useful for us. I'm going to select this and then there's three
select this and then there's three options down there. Load, transform
options down there. Load, transform data, and cancel. If I click transform
data, and cancel. If I click transform data, what's going to happen is it's
data, what's going to happen is it's going to take me into the Power Query
going to take me into the Power Query editor itself. And it's not a big deal
editor itself. And it's not a big deal if you did this. You can just go ahead
if you did this. You can just go ahead click close and apply. Now, the other
click close and apply. Now, the other option instead of hitting transform data
option instead of hitting transform data is just clicking load. And this
is just clicking load. And this basically bypasses going into that power
basically bypasses going into that power query editor and just loads it directly
query editor and just loads it directly into here as it's doing now. And then
into here as it's doing now. And then bam, we have this table inside of here.
bam, we have this table inside of here. All the different fields. I can inspect
All the different fields. I can inspect it inside the table view. And all the
it inside the table view. And all the columns look like they're coming up
columns look like they're coming up correctly. I am going to rechange the
correctly. I am going to rechange the name of this to GDP nominal. And then
name of this to GDP nominal. And then updating it there. It's also going to
updating it there. It's also going to update it inside the data pane. So now I
update it inside the data pane. So now I can make something like a map visual,
can make something like a map visual, throw in the country into the location,
throw in the country into the location, and then for the bubble size, put in
and then for the bubble size, put in that total GDP. I could also just
that total GDP. I could also just duplicate this bad boy and make it into
duplicate this bad boy and make it into a stacked bar chart. In this case, the
a stacked bar chart. In this case, the world is well everything for it. So in
world is well everything for it. So in this visual itself, I could do something
this visual itself, I could do something like just filter out world by unchecking
like just filter out world by unchecking it and bam. Pretty crazy how we can just
it and bam. Pretty crazy how we can just now get this data from online directly
now get this data from online directly into our PowerBI file and then next year
into our PowerBI file and then next year or then the following year whenever this
or then the following year whenever this data updates all we got to do is go and
data updates all we got to do is go and click refresh assuming the table name
click refresh assuming the table name doesn't change it will go forward with
doesn't change it will go forward with refreshing and getting that updated
refreshing and getting that updated data.
Now, let's get into demoing how we can connect to a data source such as a
connect to a data source such as a folder as we did in that first exercise
folder as we did in that first exercise in this video. For this, I'm going to
in this video. For this, I'm going to start a new page that we can build any
start a new page that we can build any visualizations on. And we're going to go
visualizations on. And we're going to go into get data. And for this, I'm going
into get data. And for this, I'm going to go to more. And inside of here, I'm
to go to more. And inside of here, I'm going to type in folder. Now, there's
going to type in folder. Now, there's actually two options for folder. Folder
actually two options for folder. Folder itself, which is a folder on your local
itself, which is a folder on your local machine, and SharePoint folder. If
machine, and SharePoint folder. If you're using the Microsoft ecosystem,
you're using the Microsoft ecosystem, this is what I've used in the past where
this is what I've used in the past where basically I've had another stakeholder
basically I've had another stakeholder that was in charge of the data and they
that was in charge of the data and they were just in part in charge of putting
were just in part in charge of putting the data into the SharePoint folder and
the data into the SharePoint folder and then in PowerBI service it would
then in PowerBI service it would automatically update from there. We're
automatically update from there. We're not going to be working with SharePoint
not going to be working with SharePoint folder because I'm assuming you don't
folder because I'm assuming you don't have access to it. I don't even have
have access to it. I don't even have access to it. For this exercise, we're
access to it. For this exercise, we're going to be using the data folder,
going to be using the data folder, specifically these monthly files.
specifically these monthly files. Remember, we have files broken up for
Remember, we have files broken up for the same data broken up over every
the same data broken up over every single month. Anyway, for this example,
single month. Anyway, for this example, I'm going to start by only uploading
I'm going to start by only uploading these first three months. So, I'm going
these first three months. So, I'm going to just move these other ones out. Put
to just move these other ones out. Put them on my desktop for now. And I
them on my desktop for now. And I thought it was going to delete it for it
thought it was going to delete it for it moved it out of there. Apparently, it
moved it out of there. Apparently, it doesn't. So, I'm going to delete it by
doesn't. So, I'm going to delete it by right clicking, select delete. Yes, I
right clicking, select delete. Yes, I want to delete cuz I have copies on my
want to delete cuz I have copies on my desktop. All right, let's get into
desktop. All right, let's get into importing in this folder. So, I'm going
importing in this folder. So, I'm going to go into folder and click connect.
to go into folder and click connect. From there, you're going to navigate to
From there, you're going to navigate to where the folder is with the correct
where the folder is with the correct path in there. I'm going to click okay.
path in there. I'm going to click okay. And then we have this navigator window
And then we have this navigator window pop open. And in this, we can see
pop open. And in this, we can see basically the rows here are outlining
basically the rows here are outlining the three separate files or three Excel
the three separate files or three Excel files that we have in there, right?
files that we have in there, right? Because if I navigate to that folder on
Because if I navigate to that folder on my desktop, I see that yeah, it does
my desktop, I see that yeah, it does match those three files. But how we're
match those three files. But how we're going to combine it? Well, we'll get to
going to combine it? Well, we'll get to that. Anyway, we've gone over these
that. Anyway, we've gone over these buttons before. of transform data,
buttons before. of transform data, right? Because if we've transformed it,
right? Because if we've transformed it, we're going to enter the power query
we're going to enter the power query adder. They also have this load. If we
adder. They also have this load. If we were to click load, which is not
were to click load, which is not actually what we want to do, it's going
actually what we want to do, it's going to load all these monthly files in. But
to load all these monthly files in. But this is going to be basically in a
this is going to be basically in a table, meaning navigating to the table
table, meaning navigating to the table view, it just tells us about the Excel
view, it just tells us about the Excel file. It doesn't give us the data. It
file. It doesn't give us the data. It didn't combine it. So, I'm actually
didn't combine it. So, I'm actually going to just go ahead and delete this
going to just go ahead and delete this from model and start over again. And
from model and start over again. And then back to navigating through all
then back to navigating through all those steps to load it in. In this case,
those steps to load it in. In this case, I'm not going to do load or transform.
I'm not going to do load or transform. I'm going to go into combine. And then
I'm going to go into combine. And then it says, hey, you can combine and
it says, hey, you can combine and transform data or combine and load data.
transform data or combine and load data. Like I said, we don't want to get I'm
Like I said, we don't want to get I'm not going into the Power Query out of
not going into the Power Query out of this lesson. So, we're just going to go
this lesson. So, we're just going to go to combine and load. Now, there's a
to combine and load. Now, there's a couple more steps we have to navigate
couple more steps we have to navigate to. We need to select the object to be
to. We need to select the object to be extracted from each file. In this case,
extracted from each file. In this case, we're going to collect uh select this
we're going to collect uh select this sheet one and it's using the first file.
sheet one and it's using the first file. We could also call out a specific one
We could also call out a specific one like I could call out January in this
like I could call out January in this case and click this as well. I recommend
case and click this as well. I recommend just doing first file in case January
just doing first file in case January ever gets replaced. So, I'm going to go
ever gets replaced. So, I'm going to go ahead and change it. Select sheet one
ahead and change it. Select sheet one and then select okay. And now it's going
and then select okay. And now it's going through the mo loading process of
through the mo loading process of accessing each of these monthly files.
accessing each of these monthly files. As you see, it did March, February, and
As you see, it did March, February, and now January. Inspecting the monthly
now January. Inspecting the monthly files underneath the table view. I can
files underneath the table view. I can see that it looks like we have 156,000
see that it looks like we have 156,000 rows, which sounds about right. So to
rows, which sounds about right. So to visualize it, I create a stack bar
visualize it, I create a stack bar chart, put job title short into the
chart, put job title short into the y-axis, and then the count of job title
y-axis, and then the count of job title short into the x-axis. But let's
short into the x-axis. But let's actually view this over time. time. So,
actually view this over time. time. So, I'm going to insert in a line chart and
I'm going to insert in a line chart and we'll throw job posted date into the
we'll throw job posted date into the x-axis and then count into the y-axis.
x-axis and then count into the y-axis. If you notice from this, this count is
If you notice from this, this count is this this line chart is just okay, this
this this line chart is just okay, this is a mess to look at. And the problem is
is a mess to look at. And the problem is that that job posted date is not in a
that that job posted date is not in a date format. We can actually fix this in
date format. We can actually fix this in power query editor. Like I said, we're
power query editor. Like I said, we're staying out of that today. So for the
staying out of that today. So for the time being I'm just going to select this
time being I'm just going to select this and change the format to a data type of
and change the format to a data type of date time says hey do I want to change
date time says hey do I want to change this? Yeah I want to change it. It'll
this? Yeah I want to change it. It'll say hey one or more calculate objects
say hey one or more calculate objects need to be manually refreshed. Refresh
need to be manually refreshed. Refresh them now. And now I'm going to X out of
them now. And now I'm going to X out of this with job post to date. As we can
this with job post to date. As we can see job posted date now has a date
see job posted date now has a date hierarchy. So whenever I drag it onto
hierarchy. So whenever I drag it onto here it's aggregating it by day and by
here it's aggregating it by day and by month and by year. So drilling on down I
month and by year. So drilling on down I like this day view. This is good. Now,
like this day view. This is good. Now, what happens if we get more files? Well,
what happens if we get more files? Well, whenever we add them into here, they're
whenever we add them into here, they're now in this folder, but this this still
now in this folder, but this this still needs to refresh, right? So, remember,
needs to refresh, right? So, remember, we have to still click refresh all
we have to still click refresh all tables, and it's going to go into
tables, and it's going to go into monthly files, specifically into the
monthly files, specifically into the queries. And in this case, it's going to
queries. And in this case, it's going to access each of those. Right now, it's
access each of those. Right now, it's August, November, May. And then we have
August, November, May. And then we have all of it for the year. And this is just
all of it for the year. And this is just unreadable. some navigate up one and
unreadable. some navigate up one and we'll be able to see it on a monthly
we'll be able to see it on a monthly basis. Now,
basis. Now, the last example we're going to get to
the last example we're going to get to is like I said the most real world
is like I said the most real world example of connecting to a database.
example of connecting to a database. Specifically, we're going to get and
Specifically, we're going to get and connect to the database behind data.te.
connect to the database behind data.te. This app, which has collected up to 3.6
This app, which has collected up to 3.6 million jobs at the time of filming
million jobs at the time of filming this, has all of this in a database.
this, has all of this in a database. Specifically, it's a big query database.
Specifically, it's a big query database. Actually, just to prove that I have
Actually, just to prove that I have access to it, here I am inside of my
access to it, here I am inside of my Google Cloud account. I'm connected to
Google Cloud account. I'm connected to the table itself. Here's all the
the table itself. Here's all the different columns. Has a lot more
different columns. Has a lot more columns than you're used to seeing.
columns than you're used to seeing. Anyway, the details inside of it. It has
Anyway, the details inside of it. It has 3.6 million rows inside of it. I can
3.6 million rows inside of it. I can also, if I wanted to, see a preview of
also, if I wanted to, see a preview of the data within it. Anyway, we're going
the data within it. Anyway, we're going to use Power Query to connect to this
to use Power Query to connect to this online database. And by we, I mean me.
online database. And by we, I mean me. Unfortunately, it would cost entirely
Unfortunately, it would cost entirely too much money to try to get everybody
too much money to try to get everybody in account access. Also, I'd have to pay
in account access. Also, I'd have to pay for the resources for everybody
for the resources for everybody accessing it. It just be a giant
accessing it. It just be a giant headache. Sorry, it's only going to be
headache. Sorry, it's only going to be me. Anyway, I'm going to click get data
me. Anyway, I'm going to click get data and then more. And then from there,
and then more. And then from there, you're going to search for whatever
you're going to search for whatever database you have it in. In my case, I
database you have it in. In my case, I use BigQuery. So, I'm going to select
use BigQuery. So, I'm going to select BigQuery and select connect. From there,
BigQuery and select connect. From there, I'm going to specify all of my
I'm going to specify all of my connection information. I can also give
connection information. I can also give a SQL statement if I want to get maybe a
a SQL statement if I want to get maybe a subset of the data. Now, what you didn't
subset of the data. Now, what you didn't see prior to this is I actually had to
see prior to this is I actually had to go through log into Google and provide
go through log into Google and provide my credentials to access it. So, there
my credentials to access it. So, there is another step to get to to make sure
is another step to get to to make sure that just nobody can access your
that just nobody can access your database. Anyway, I navigated into the
database. Anyway, I navigated into the table itself and looking at it, it looks
table itself and looking at it, it looks like it's right. I could verify by going
like it's right. I could verify by going back to BigQuery, checking it out and be
back to BigQuery, checking it out and be like, "Yeah, that matches the columns."
like, "Yeah, that matches the columns." And then from there, we have options of
And then from there, we have options of load, transform data, i.e. open the
load, transform data, i.e. open the power query editor or cancel. I'm just
power query editor or cancel. I'm just going to load it in. Now, this is
going to load it in. Now, this is something new that we haven't covered
something new that we haven't covered yet. And it's asking me how do I want to
yet. And it's asking me how do I want to basically bring all this data in. Do I
basically bring all this data in. Do I want to import it or do I want to direct
want to import it or do I want to direct query it? Now, in all of our previous
query it? Now, in all of our previous example, we've always used import mode.
example, we've always used import mode. But we've never been given the option to
But we've never been given the option to do direct query. And import mode just
do direct query. And import mode just means we import in all the data. Now
means we import in all the data. Now direct query does not import it in
direct query does not import it in meaning the file size is much smaller.
meaning the file size is much smaller. The PowerBI file size is much smaller.
The PowerBI file size is much smaller. And then every time that you want to
And then every time that you want to maybe update a visualization, it has to
maybe update a visualization, it has to go out and get that data. So therefore
go out and get that data. So therefore with performance for import mode, it's
with performance for import mode, it's very fast. For direct query, super slow
very fast. For direct query, super slow depending on how big the data source is.
depending on how big the data source is. Import mode supports basically all our
Import mode supports basically all our different functionality. Yes, you have
different functionality. Yes, you have to manually refresh inside the PowerBI
to manually refresh inside the PowerBI app, but you can also set that up in the
app, but you can also set that up in the service. Direct query doesn't support
service. Direct query doesn't support other advanced features such as like
other advanced features such as like accessing this data while you're offline
accessing this data while you're offline or supporting full DAX, which we'll be
or supporting full DAX, which we'll be demonstrating in chapter 4. Anyway, the
demonstrating in chapter 4. Anyway, the point is you have to raise your costs
point is you have to raise your costs and your benefits of what you want to
and your benefits of what you want to actually accomplish with this. I have
actually accomplish with this. I have 3.6 million rows of data to get into
3.6 million rows of data to get into here. that would make this a heck of a
here. that would make this a heck of a size of a file and so I'm okay with
size of a file and so I'm okay with being a little bit slower and I'm going
being a little bit slower and I'm going to go with direct query. Now let's get
to go with direct query. Now let's get into inspecting it. If I wanted to or
into inspecting it. If I wanted to or what I can't actually do if I went to
what I can't actually do if I went to table view I can't view it because it's
table view I can't view it because it's not an import mo mode. It's in that
not an import mo mode. It's in that direct query. So unfortunately
direct query. So unfortunately everything I want to view from it I have
everything I want to view from it I have to do from the canvas. So I select a new
to do from the canvas. So I select a new card and I'm going to drag the job ID
card and I'm going to drag the job ID into the fields. And specifically I want
into the fields. And specifically I want a count of this. And this tells me I
a count of this. And this tells me I have 3.65
have 3.65 million jobs. Let's add a few more
million jobs. Let's add a few more visualizations. And bam, we get this bad
visualizations. And bam, we get this bad boy. So, I'm able to look at all the
boy. So, I'm able to look at all the different values we've looked at
different values we've looked at previously.
previously. But I will show something with this. If
But I will show something with this. If I'm trying to actually cross filter, in
I'm trying to actually cross filter, in this case, I selected software engineer.
this case, I selected software engineer. You can see everything is going through
You can see everything is going through and trying to load with 3.6 million rows
and trying to load with 3.6 million rows in a database. This is going to take a
in a database. This is going to take a little bit of time. And it looks like
little bit of time. And it looks like it's finally updated. I still have one
it's finally updated. I still have one more. Okay, everything's now loaded.
more. Okay, everything's now loaded. Now, if I wanted to at any point, if I
Now, if I wanted to at any point, if I wanted to switch this from that direct
wanted to switch this from that direct query into import mode, I could come
query into import mode, I could come down here to storage mode and say, "Hey,
down here to storage mode and say, "Hey, switch all tables to import." Once you
switch all tables to import." Once you do this though, you can't revert back to
do this though, you can't revert back to the direct query. Now, with direct
the direct query. Now, with direct query, we were able to load this in. You
query, we were able to load this in. You mean you saw how fast we went through
mean you saw how fast we went through the data source. I'm going through right
the data source. I'm going through right now, and it's loading in the rows. Look
now, and it's loading in the rows. Look at this. is at 350,000
at this. is at 350,000 and we still have to get to 3.6 million.
and we still have to get to 3.6 million. Also, we're still loading the data. So,
Also, we're still loading the data. So, the file hasn't updated uh necessarily
the file hasn't updated uh necessarily just yet, but just for reference to
just yet, but just for reference to remember this, right, the data size of
remember this, right, the data size of the file right now is at 11 megabytes.
the file right now is at 11 megabytes. And we're still loading. And it looks
And we're still loading. And it looks like we're wrapping up these rows of
like we're wrapping up these rows of this database. All right. So, truth be
this database. All right. So, truth be told, I got done with or was getting
told, I got done with or was getting close to loading and that file end up
close to loading and that file end up crashing. I didn't want to go through
crashing. I didn't want to go through that reload process again. So, I opened
that reload process again. So, I opened an old file that I worked with
an old file that I worked with previously. This one is connected with
previously. This one is connected with direct import to that database. This one
direct import to that database. This one only has 3.49 million cuz I did this a
only has 3.49 million cuz I did this a month ago. Anyway, it still has all the
month ago. Anyway, it still has all the data inside of here. But notice how fast
data inside of here. But notice how fast whenever I actually click this, how fast
whenever I actually click this, how fast it actually filters down because it's
it actually filters down because it's imported in. Now, there's a major
imported in. Now, there's a major drawback from that. Remember, our
drawback from that. Remember, our previous file was only 11 megabytes.
previous file was only 11 megabytes. This bad boy is 2500
This bad boy is 2500 megabytes.
megabytes. So nearly 200 times bigger. So importing
So nearly 200 times bigger. So importing a database isn't necessarily as simple
a database isn't necessarily as simple as importing a database cuz sometimes
as importing a database cuz sometimes you have to decide if you're going to
you have to decide if you're going to use import mode or direct query. How's
use import mode or direct query. How's it going to affect a performance or how
it going to affect a performance or how that's going to affect file size. My
that's going to affect file size. My recommendation is you just use import
recommendation is you just use import and if you can clean up your data into
and if you can clean up your data into as smallest size as possible before
as smallest size as possible before actually bring it into PowerBI. If
actually bring it into PowerBI. If that's not an option, go with direct
that's not an option, go with direct query. All right. So, now that we have
query. All right. So, now that we have that in-depth coverage of how we can
that in-depth coverage of how we can import databases, but also other data
import databases, but also other data sources as well, we now have some
sources as well, we now have some practice problems for you to go through
practice problems for you to go through and connect to some other different data
and connect to some other different data sources as well. With that, in the next
sources as well. With that, in the next lesson, we're going to be jumping into
lesson, we're going to be jumping into the Power Query editor. See you there.
Now that we're master at understanding what are all the different types of data
what are all the different types of data sources we can connect to. Now let's
sources we can connect to. Now let's jump into the Power Query editor itself
jump into the Power Query editor itself and actually get to cleaning up some
and actually get to cleaning up some data. Now in this video we're going to
data. Now in this video we're going to be performing cleanup of our CSV file
be performing cleanup of our CSV file that we've previously been using and
that we've previously been using and we're going to do that with the Power
we're going to do that with the Power Query editor while exploring it. Anyway,
Query editor while exploring it. Anyway, the first case we're going to take
the first case we're going to take advantage of, as we saw previously, that
advantage of, as we saw previously, that job posted date time. Whenever we drag
job posted date time. Whenever we drag it into a line chart, it doesn't do it
it into a line chart, it doesn't do it because the data wasn't correct in being
because the data wasn't correct in being in a hierarchy or recognizes date time
in a hierarchy or recognizes date time as it was here. Demoed that in the last
as it was here. Demoed that in the last lesson. Anyway, we're going to use Power
lesson. Anyway, we're going to use Power Query to actually clean up this column.
Query to actually clean up this column. The other thing we're going to do, which
The other thing we're going to do, which is quite common with Power Query, is
is quite common with Power Query, is create new columns that we can then
create new columns that we can then analyze further with. Specifically here,
analyze further with. Specifically here, we're going to be analyzing a column
we're going to be analyzing a column called salary hour adjusted. And that
called salary hour adjusted. And that adjusted column is going to take our
adjusted column is going to take our salary hour average column and multiply
salary hour average column and multiply it times 2080 or basically 40 hours
it times 2080 or basically 40 hours times 52 weeks in a year. And therefore
times 52 weeks in a year. And therefore we can understand what would be the
we can understand what would be the yearly salary based on an hourly pay.
yearly salary based on an hourly pay. Anyway, we're going to make these charts
Anyway, we're going to make these charts associated with it. And this allows us
associated with it. And this allows us now to compare yearly median salary to
now to compare yearly median salary to now hourly adjusted salary like we're
now hourly adjusted salary like we're doing in this line chart.
doing in this line chart. So let's not get ahead of oursel. We're
So let's not get ahead of oursel. We're going to get an intro now into the Power
going to get an intro now into the Power Query editor. And for this lesson, feel
Query editor. And for this lesson, feel free to just start a new blank report.
free to just start a new blank report. Inside out of our new file, let's
Inside out of our new file, let's connect to our previous CSV that we've
connect to our previous CSV that we've been using. Selecting this of text CSV
been using. Selecting this of text CSV and then navigating to the data source
and then navigating to the data source itself of job postings flat. Select
itself of job postings flat. Select open. Inside the navigator window,
open. Inside the navigator window, remember we don't want to go to load. We
remember we don't want to go to load. We want to actually we're going to explore
want to actually we're going to explore the power query editor itself. So we're
the power query editor itself. So we're going to go into transform data. So,
going to go into transform data. So, let's go over this UI of this Power
let's go over this UI of this Power Query editor that just opened up. It has
Query editor that just opened up. It has a very similar format to all Microsoft
a very similar format to all Microsoft products in that up at the top, we have
products in that up at the top, we have the ribbon itself. Then underneath this,
the ribbon itself. Then underneath this, we have the data view area. And it may
we have the data view area. And it may be confusing to some cuz it looks like
be confusing to some cuz it looks like it's Excel, but I can't go in here and
it's Excel, but I can't go in here and like try like I'm trying to I can't type
like try like I'm trying to I can't type inside of here. This is just showing me
inside of here. This is just showing me what is the current view view of the
what is the current view view of the query that we're operating on. So this
query that we're operating on. So this has all the different columns of our
has all the different columns of our final data set. With this we have a
final data set. With this we have a queries pane over to the left hand side.
queries pane over to the left hand side. So we're currently operating on the job
So we're currently operating on the job postings flat query which is this query.
postings flat query which is this query. Conveniently they just named it this
Conveniently they just named it this based on our CSV. And then over here on
based on our CSV. And then over here on the right hand side is our query
the right hand side is our query settings. And notice here, so we have
settings. And notice here, so we have our name right here. If I wanted to, I
our name right here. If I wanted to, I could name it to just job postings.
could name it to just job postings. Click enter. And then our query itself
Click enter. And then our query itself updates that. I want job postings flat,
updates that. I want job postings flat, so we're going to leave it as that. And
so we're going to leave it as that. And then underneath this, we have what steps
then underneath this, we have what steps were applied in Power Query for this. So
were applied in Power Query for this. So I can actually go back into previous
I can actually go back into previous steps. Right now, we're on change type.
steps. Right now, we're on change type. That's the last and most recent step. I
That's the last and most recent step. I can go to promoted headers. And in this
can go to promoted headers. And in this one, there's not really much of a
one, there's not really much of a difference. But if I go into the source
difference. But if I go into the source step, we can actually see that from the
step, we can actually see that from the source itself, it imported in and those
source itself, it imported in and those job titles or sorry the uh actual column
job titles or sorry the uh actual column headers were on row one. So that's why
headers were on row one. So that's why it went through once it did the source,
it went through once it did the source, then it went into promoted headers and
then it went into promoted headers and then finally into change type. Sometime
then finally into change type. Sometime to access the properties within here,
to access the properties within here, you need to click this settings icon. So
you need to click this settings icon. So in the case of the promoted headers, I
in the case of the promoted headers, I would click this and then I could select
would click this and then I could select different options. We're not going to
different options. We're not going to change anything for these so far. All
change anything for these so far. All right. So that's the main portions of
right. So that's the main portions of this. One last thing to call out after
this. One last thing to call out after this query setup now that we've seen it.
this query setup now that we've seen it. Notice there's a formula bar up here.
Notice there's a formula bar up here. And if I go to this like change type,
And if I go to this like change type, the formula inside of here actually
the formula inside of here actually changes. Anyway, this itself inside of
changes. Anyway, this itself inside of here is what's called the M language.
here is what's called the M language. Power Query has a special language
Power Query has a special language that's put together to basically compile
that's put together to basically compile all the different steps to build this
all the different steps to build this query. If I wanted to go check it out, I
query. If I wanted to go check it out, I can go into this advanced editor up here
can go into this advanced editor up here and this is the full query for this
and this is the full query for this actual data set or this query. But once
actual data set or this query. But once again, we're getting ahead of oursel.
So, we're going to start with a going over the view tab first. And it's
over the view tab first. And it's important for that because sometimes
important for that because sometimes people think that, oh, I'm doing edits
people think that, oh, I'm doing edits in here. I can't actually evaluate and
in here. I can't actually evaluate and find out what's going until I go back to
find out what's going until I go back to the home tab and then close and apply to
the home tab and then close and apply to therefore load it into PowerBI. But
therefore load it into PowerBI. But actually with this view tab, we can do a
actually with this view tab, we can do a lot of analysis here and prevent us from
lot of analysis here and prevent us from having to jump back and forth between
having to jump back and forth between the Power Query editor and the PowerBI
the Power Query editor and the PowerBI app. What do I mean by that? Okay. Well,
app. What do I mean by that? Okay. Well, let's actually go check out something
let's actually go check out something like the job title short column. Now,
like the job title short column. Now, what's really neat about this is we have
what's really neat about this is we have up at the top here some icons that say,
up at the top here some icons that say, hey, we have 10 distinct value and zero
hey, we have 10 distinct value and zero unique. And if you actually count these
unique. And if you actually count these bars, that's the 10 distinct values. And
bars, that's the 10 distinct values. And we know from exploring the job title
we know from exploring the job title short column before that if I were to
short column before that if I were to actually use this drop- down arrow here,
actually use this drop- down arrow here, there are 10 values in here.
there are 10 values in here. Specifically, there's 10 different job
Specifically, there's 10 different job titles. Now, this drop- down arrow, now
titles. Now, this drop- down arrow, now that we have it open, it works similar
that we have it open, it works similar to how you could filter in Excel. I can
to how you could filter in Excel. I can sort ascending, sort descending. I'll do
sort ascending, sort descending. I'll do sort descending. Right now, it's going
sort descending. Right now, it's going to go through a load process. And if you
to go through a load process. And if you notice, we have an applied step of
notice, we have an applied step of sorted rows, but now it's uh sorted in
sorted rows, but now it's uh sorted in descending order. And it's now saying
descending order. And it's now saying there's only one distinct value. Why the
there's only one distinct value. Why the heck is that? Well, let's actually
heck is that? Well, let's actually inspect this. So, selecting the job tile
inspect this. So, selecting the job tile short column using the view tab. What I
short column using the view tab. What I can do here is come up here and select
can do here is come up here and select something like the column profile. This
something like the column profile. This thing is invaluable. Like I said,
thing is invaluable. Like I said, invaluable. I mean, invaluable. Anyway,
invaluable. I mean, invaluable. Anyway, what we find out is, yeah, everything
what we find out is, yeah, everything the software engineer makes up
the software engineer makes up everything. But it says, hey, the
everything. But it says, hey, the software engineer makes up 100% but a
software engineer makes up 100% but a thousand of them are software engineers.
thousand of them are software engineers. What's going on is I'm going to actually
What's going on is I'm going to actually close out of column profiling real
close out of column profiling real quick. Column profiling is based on the
quick. Column profiling is based on the top 1,00 rows at least selected from the
top 1,00 rows at least selected from the bottom. What I can do is change this to
bottom. What I can do is change this to the entire data set. Now, this is going
the entire data set. Now, this is going to actually have to load more data now
to actually have to load more data now and so it's going to take some time. So
and so it's going to take some time. So that's why by default it's set to a
that's why by default it's set to a th00and values because sometimes it
th00and values because sometimes it takes a while to actually load depending
takes a while to actually load depending on how big the data set is. So it loaded
on how big the data set is. So it loaded and now we can see that this preview
and now we can see that this preview area shows that there is 10 unique
area shows that there is 10 unique values. Whenever I go to column profile
values. Whenever I go to column profile and actually look inside the job tile
and actually look inside the job tile short column, I can see there's almost
short column, I can see there's almost 500,000 jobs here. And we actually see
500,000 jobs here. And we actually see all the different jobs, not just those
all the different jobs, not just those software engineers since we had it
software engineers since we had it sorted in descending order. And you can
sorted in descending order. And you can do this with any column. I can just go
do this with any column. I can just go through here and select different
through here and select different columns that I want to actually view. In
columns that I want to actually view. In this case, I'm looking at job location.
this case, I'm looking at job location. I can see that anywhere comprises nearly
I can see that anywhere comprises nearly 13% of jobs. Some more things to explore
13% of jobs. Some more things to explore up here from this view tab. I'm going to
up here from this view tab. I'm going to turn off that column profile. But we
turn off that column profile. But we also have this column distribution
also have this column distribution enabled. I can uncheck that or check
enabled. I can uncheck that or check that. I like to have that visually so I
that. I like to have that visually so I don't have to necessarily open the
don't have to necessarily open the column profile to view that. We have
column profile to view that. We have this of column quality which you can see
this of column quality which you can see that it tells you which data is valid,
that it tells you which data is valid, which one's the error, which one's
which one's the error, which one's empty. I'm not a fan of this because you
empty. I'm not a fan of this because you can actually, if you look up here at the
can actually, if you look up here at the top, there's a bar right here that shows
top, there's a bar right here that shows that. And we can see this a little bit
that. And we can see this a little bit more clearly using this these three
more clearly using this these three columns here where for something like
columns here where for something like the salary rate or salary year average,
the salary rate or salary year average, nearly 96% of them are empty, hence the
nearly 96% of them are empty, hence the gray bar. And then the other 4% are
gray bar. And then the other 4% are valid. Anyway, this bar is located up
valid. Anyway, this bar is located up here. Because of that, I don't really
here. Because of that, I don't really care about column quality. The other two
care about column quality. The other two of monospace just changes the font tape
of monospace just changes the font tape or displays or doesn't display whites
or displays or doesn't display whites space. I just leave show whites space
space. I just leave show whites space collect. Navigating back over to job
collect. Navigating back over to job tile short. Remember, we do have it
tile short. Remember, we do have it right now sorted. I can tell there's a
right now sorted. I can tell there's a sort on there. I actually didn't want to
sort on there. I actually didn't want to apply that step. If I want to remove a
apply that step. If I want to remove a step, I just navigate to whatever one,
step, I just navigate to whatever one, in this case, sorted rows, click this
in this case, sorted rows, click this red X right here, and it gets rid of it.
red X right here, and it gets rid of it. I also, it's taking a while for this
I also, it's taking a while for this data set to load in between each one.
data set to load in between each one. So, I'm going to change this column
So, I'm going to change this column profiling back to the top 1,000 rows.
profiling back to the top 1,000 rows. And with that, the last thing to capture
And with that, the last thing to capture on this column distribution, remember we
on this column distribution, remember we talked about here there was 10 distinct
talked about here there was 10 distinct values and zero unique, which distinct
values and zero unique, which distinct means they have repeating values. Unique
means they have repeating values. Unique means that there's only that value once.
means that there's only that value once. So in the case of job location of these
So in the case of job location of these top 10,00 values, there's 48 distinct
top 10,00 values, there's 48 distinct values, so repeating values, and 277
values, so repeating values, and 277 unique, but that's only for the top
unique, but that's only for the top thousand.
Jumping next into the home tab on the ribbon. This is where I spend the
ribbon. This is where I spend the majority of my time selecting different
majority of my time selecting different options that I want to do with cleaning
options that I want to do with cleaning up my data. We're going to be exploring
up my data. We're going to be exploring all of these features over the course of
all of these features over the course of the chapter, but I'm not going to dive
the chapter, but I'm not going to dive into each individual one because then
into each individual one because then this video would be too long and you're
this video would be too long and you're not going to pay attention. So, instead,
not going to pay attention. So, instead, we're just going to highlight key things
we're just going to highlight key things that I'm using very frequently with this
that I'm using very frequently with this specifically. If we go over to that job
specifically. If we go over to that job posted date column, we can see that it
posted date column, we can see that it is of the date time using this home
is of the date time using this home ribbon date time, which if you remember
ribbon date time, which if you remember from the last lesson, it didn't
from the last lesson, it didn't automatically select this because we
automatically select this because we didn't go through the power query editor
didn't go through the power query editor for the transformation. Anyway, not a
for the transformation. Anyway, not a big deal. The main point of showing is
big deal. The main point of showing is we can control the data type. And in
we can control the data type. And in here, it automatically did select job
here, it automatically did select job posted date as a date time. So, let's
posted date as a date time. So, let's actually demo a use case where we
actually demo a use case where we actually change a value. In this case, I
actually change a value. In this case, I can select the salary year average
can select the salary year average column. In our case, it is whole number.
column. In our case, it is whole number. And this value, as we can see here, it's
And this value, as we can see here, it's like 120,000. We're a salary hour
like 120,000. We're a salary hour average. It is of the data type decimal
average. It is of the data type decimal number. And we can see that it actually
number. And we can see that it actually has decimal numbers associated with it.
has decimal numbers associated with it. If I also want to get salary year
If I also want to get salary year average into this format, I would just
average into this format, I would just click decimal number. And it's asking me
click decimal number. And it's asking me this important step. Hey, do I want to
this important step. Hey, do I want to replace the current applied step? So
replace the current applied step? So this change type or do I want to add a
this change type or do I want to add a new step? Let's do add a new step. Just
new step? Let's do add a new step. Just a demo. It adds another step underneath
a demo. It adds another step underneath here. And all that's done here with this
here. And all that's done here with this change type one selected is a change
change type one selected is a change salary year average to type number. Now
salary year average to type number. Now I'm not a big fan of creating additional
I'm not a big fan of creating additional steps in here because there can be times
steps in here because there can be times where we get to we have 15 or 20 applied
where we get to we have 15 or 20 applied test sets. We want to minimize this as
test sets. We want to minimize this as much as possible. So I'm going to click
much as possible. So I'm going to click X out of this and we're going to do this
X out of this and we're going to do this again. with the salary or average column
again. with the salary or average column selected. Change it to decimal number.
selected. Change it to decimal number. And in this case, we're going to go
And in this case, we're going to go ahead with replace current and it's
ahead with replace current and it's updated cuz I can see it says decimal
updated cuz I can see it says decimal number up here. Along within this M
number up here. Along within this M language for the formula bar, it updated
language for the formula bar, it updated to the type number. I actually don't
to the type number. I actually don't want this as a decimal. We're going to
want this as a decimal. We're going to change this back to a whole number.
change this back to a whole number. We're going to replace current as well.
We're going to replace current as well. and salary year average changed back
and salary year average changed back into what it was originally for whole
into what it was originally for whole number which is this characteristic of
number which is this characteristic of in64.type type. Not something you need
in64.type type. Not something you need to have memorized. I just like to
to have memorized. I just like to sometimes look at the M language,
sometimes look at the M language, understand what's going on there. But
understand what's going on there. But clearly, we can see from this columns
clearly, we can see from this columns are put inside of parentheses and then
are put inside of parentheses and then referenced as necessary. So that's the
referenced as necessary. So that's the home tab. We're going to be going into a
home tab. We're going to be going into a lot of these other features,
lot of these other features, specifically manage columns, reduce
specifically manage columns, reduce rows, and everything else under
rows, and everything else under transform and some upcoming lessons.
Moving into the transform tab here. And with this, you're going to see a lot of
with this, you're going to see a lot of stuff repeated from the home tab.
stuff repeated from the home tab. Specifically right here, right? I see
Specifically right here, right? I see the salary year average. I can control
the salary year average. I can control the data type from here. Anyway, this
the data type from here. Anyway, this tab itself, it allows us to do more
tab itself, it allows us to do more control of how we want to modify a
control of how we want to modify a column. Let's take for example this job
column. Let's take for example this job via column, which shows us the platform
via column, which shows us the platform in which a job posted was posted on. If
in which a job posted was posted on. If I inspect it using column profile, I can
I inspect it using column profile, I can see that these different platforms have
see that these different platforms have the word via and then a space in front
the word via and then a space in front of it. If I'm trying to present this to
of it. If I'm trying to present this to my boss, I really don't want this via
my boss, I really don't want this via space in front of it. I just want it to
space in front of it. I just want it to say like in this case the second one,
say like in this case the second one, LinkedIn. Well, that's where the
LinkedIn. Well, that's where the transform tab comes to the rescue. With
transform tab comes to the rescue. With job via selected, I can go into replace
job via selected, I can go into replace values. Specifically, I want to replace
values. Specifically, I want to replace via with well with nothing. I'm gonna go
via with well with nothing. I'm gonna go ahead and click okay. So, this removed
ahead and click okay. So, this removed the via. But if I actually click
the via. But if I actually click something like this of boingsreveal.com,
something like this of boingsreveal.com, I'd have to actually check out this job
I'd have to actually check out this job posting website. Anyway, it shows down
posting website. Anyway, it shows down here at the bottom. But whenever you
here at the bottom. But whenever you highlight it, what you don't what you do
highlight it, what you don't what you do see is there's actually some white space
see is there's actually some white space in front of here. and I highlighted it
in front of here. and I highlighted it here. What we could do is we could do
here. What we could do is we could do one more step and in this case we want
one more step and in this case we want to have with the job via column selected
to have with the job via column selected go to format and I can do things like
go to format and I can do things like lower cases which is demonstrated here.
lower cases which is demonstrated here. I could even uppercase it make
I could even uppercase it make everything uppercase. I'm going to
everything uppercase. I'm going to delete both these steps. It's not what I
delete both these steps. It's not what I want to do. Instead what I want to do is
want to do. Instead what I want to do is I want to trim it. And now with this
I want to trim it. And now with this selected we can see that there's no
selected we can see that there's no white space in front of this. Now this
white space in front of this. Now this is actually unnecessary. I'm mainly just
is actually unnecessary. I'm mainly just doing this for demo purposes. I'm going
doing this for demo purposes. I'm going to remove this trim text portion. And
to remove this trim text portion. And underneath replace values, go into here
underneath replace values, go into here to modify it. And for the via, I'll put
to modify it. And for the via, I'll put via and then space. And now click okay.
via and then space. And now click okay. And in this case, whenever I select it,
And in this case, whenever I select it, I can see that that white space was
I can see that that white space was removed. We don't have to do an extra
removed. We don't have to do an extra step. Minimize steps.
Next up is the add column tab. And as the name implies, this adds a column.
the name implies, this adds a column. Transform, looking at transform and then
Transform, looking at transform and then looking at add column, there's a lot of
looking at add column, there's a lot of similarities in functions between the
similarities in functions between the two. And the key difference is is
two. And the key difference is is transform does it to the column itself
transform does it to the column itself and add column adds a new column. So
and add column adds a new column. So besides just formatting text like
besides just formatting text like extracting out or cleaning up the white
extracting out or cleaning up the white space around different columns and
space around different columns and creating a new column, I could use it
creating a new column, I could use it for a use case like this in job posted
for a use case like this in job posted date. This column name is actually
date. This column name is actually slightly misleading because it says job
slightly misleading because it says job posted date, but it's a date time. So if
posted date, but it's a date time. So if I wanted to make this column into a date
I wanted to make this column into a date and then this one into something called
and then this one into something called job posted date time, I could do that.
job posted date time, I could do that. So with this selected, I'm going to
So with this selected, I'm going to select up here to change this to a date
select up here to change this to a date and specifically date only. Now I want
and specifically date only. Now I want to change this name to job posted date.
to change this name to job posted date. So I could click on it and try to enter
So I could click on it and try to enter job posted date and then press enter.
job posted date and then press enter. But it conflicts with our other name. We
But it conflicts with our other name. We have to rename the other one first. So,
have to rename the other one first. So, our original job posted date. I'm
our original job posted date. I'm actually going to change this to job
actually going to change this to job posted date time. And then change this
posted date time. And then change this one to job posted date. Now, I don't
one to job posted date. Now, I don't like where this job posted date is, like
like where this job posted date is, like how far it is from job posted date time.
how far it is from job posted date time. So, I can drag it. I can also rightclick
So, I can drag it. I can also rightclick it and select to move it. It allows me
it and select to move it. It allows me to move it to the left, right to
to move it to the left, right to beginning, end. I can move it to the
beginning, end. I can move it to the beginning. And we got this new step of
beginning. And we got this new step of reorder columns. This actually isn't
reorder columns. This actually isn't where I want it. I'm going to drag it
where I want it. I'm going to drag it over. Get there. And now it's here. Now,
over. Get there. And now it's here. Now, unfortunately, with dates or date times
unfortunately, with dates or date times of Word, go to something like column
of Word, go to something like column profile and try to visualize it. I could
profile and try to visualize it. I could even change it to something like the
even change it to something like the entire data set. I'm not going to get
entire data set. I'm not going to get much value out of this new distribution
much value out of this new distribution once all those values loaded in other
once all those values loaded in other than well, this bad boy. So there are
than well, this bad boy. So there are some cases where now in this case I
some cases where now in this case I would go close and apply it and then
would go close and apply it and then load it directly into our file. Also we
load it directly into our file. Also we haven't done it already. We need to
haven't done it already. We need to actually go in and save this. With that
actually go in and save this. With that saved, let's actually get into
saved, let's actually get into visualizing it. We're going to be making
visualizing it. We're going to be making line charts with this. Specifically, I
line charts with this. Specifically, I want to compare that job posted date
want to compare that job posted date time basically without the hierarchy. So
time basically without the hierarchy. So I'm going to rightclick this and remove
I'm going to rightclick this and remove that date hierarchy. And then we're
that date hierarchy. And then we're going to do a count of the job title
going to do a count of the job title short. Remember previously in the last
short. Remember previously in the last lesson, this is what we're seeing with
lesson, this is what we're seeing with that job posted date time whenever it
that job posted date time whenever it wasn't formatted correctly. It's a hot
wasn't formatted correctly. It's a hot mess. Not what we want to view. Anyway,
mess. Not what we want to view. Anyway, I copied and pasted this over here to
I copied and pasted this over here to the right hand side. And even if I were
the right hand side. And even if I were to put job posted date in here now, and
to put job posted date in here now, and yeah, it's working. But even when I
yeah, it's working. But even when I convert this to away from that hierarchy
convert this to away from that hierarchy itself, the values are still usable.
itself, the values are still usable. Unlike this one, not necessarily usable
Unlike this one, not necessarily usable with this datetime format. All right,
with this datetime format. All right, good enough to inspect. Let's jump back
good enough to inspect. Let's jump back into Power Query Editor. We go back into
into Power Query Editor. We go back into transform data and then transform data.
transform data and then transform data. You can also access it by clicking these
You can also access it by clicking these three dots right here for any data
three dots right here for any data source and going into edit query. All
source and going into edit query. All right, so here we are back here. There's
right, so here we are back here. There's one final cleanup I want to do, one
one final cleanup I want to do, one final exercise, if you will, and that
final exercise, if you will, and that deals with that salary hour average
deals with that salary hour average column. Oops, looks like I have column
column. Oops, looks like I have column profile turned on. I'm going to turn
profile turned on. I'm going to turn that off. Anyway, if you remember, I
that off. Anyway, if you remember, I wanted to compare or we're going to
wanted to compare or we're going to compare the salary year average column
compare the salary year average column to an adjusted val value of the salary
to an adjusted val value of the salary hour average column. Specifically,
hour average column. Specifically, salary hour average is in an hourly
salary hour average is in an hourly format. We want to get into what would
format. We want to get into what would it be for a yearly salary. So what we
it be for a yearly salary. So what we need to do is take these values inside
need to do is take these values inside of salary hour average such as this one
of salary hour average such as this one here of 61.15 and we want to multiply it
here of 61.15 and we want to multiply it times the number of hours in a week and
times the number of hours in a week and the number of weeks in a year. So we
the number of weeks in a year. So we come up here into the ad column
come up here into the ad column underneath standard. We want to multiply
underneath standard. We want to multiply this column that we have selected and
this column that we have selected and there's 40 hours in a week and 52 weeks
there's 40 hours in a week and 52 weeks in a year. This actually comes out to
in a year. This actually comes out to 2080. You have to put in actual whole
2080. You have to put in actual whole number in here for this. And we're go
number in here for this. And we're go ahead and click okay. Now, I want to
ahead and click okay. Now, I want to double check my values real quick. So,
double check my values real quick. So, I'm just going to filter real quick to
I'm just going to filter real quick to remove null. Remember, this will
remove null. Remember, this will actually apply a step here of filter
actually apply a step here of filter row. So, we'll need to remove this. And
row. So, we'll need to remove this. And then, if I drag it on over next to
then, if I drag it on over next to salary average, so we can view it. We
salary average, so we can view it. We can see that. Okay. Yeah, it did
can see that. Okay. Yeah, it did actually apply the necessary
actually apply the necessary multiplication to get the values we
multiplication to get the values we need. All right. So, let's remove these
need. All right. So, let's remove these last two steps to get back where we
last two steps to get back where we were. We just reordered it and then also
were. We just reordered it and then also filtered. And we're doing this because
filtered. And we're doing this because navigating this multiplication column. I
navigating this multiplication column. I need to rename it. And we could do this
need to rename it. And we could do this by double clicking this, typing in the
by double clicking this, typing in the name of salary, hour adjusted. I need to
name of salary, hour adjusted. I need to get that right. Click enter. And then
get that right. Click enter. And then this adds another step. Remember, I'm
this adds another step. Remember, I'm not really a big fan of adding extra
not really a big fan of adding extra steps. I'm going to go ahead and stop
steps. I'm going to go ahead and stop this or close out of that step. If I
this or close out of that step. If I select the inserted multiplication, open
select the inserted multiplication, open up this formula bar right here. Now, we
up this formula bar right here. Now, we don't need to be experts at reading this
don't need to be experts at reading this M language here, this formula bar. But
M language here, this formula bar. But what you can see, as we've seen
what you can see, as we've seen previously with something like the
previously with something like the change type, I'm going to select that
change type, I'm going to select that one. These column headers are in
one. These column headers are in parentheses.
parentheses. Similarly, if I go to insert and
Similarly, if I go to insert and multiplication and I look at this column
multiplication and I look at this column header is in parenthesis, these two
header is in parenthesis, these two match. So for this step of insert
match. So for this step of insert multiplication, it's giving it this
multiplication, it's giving it this name. Instead, I could change it up here
name. Instead, I could change it up here to salary hour adjusted. Press enter and
to salary hour adjusted. Press enter and then it does it within the same step and
then it does it within the same step and there's no extra step or applied step.
there's no extra step or applied step. Now I could take salary hour adjusted
Now I could take salary hour adjusted and drag it over here. next to salary
and drag it over here. next to salary hour average. And I'm gonna get nitpicky
hour average. And I'm gonna get nitpicky because I I really like minimizing my
because I I really like minimizing my steps. If you've noticed right now, we
steps. If you've noticed right now, we have two separate reorder columns. We
have two separate reorder columns. We know that the the we have multiple of it
know that the the we have multiple of it because it now says reordered columns
because it now says reordered columns one. My recommendation instead, this is
one. My recommendation instead, this is an advanced technique. Don't worry if
an advanced technique. Don't worry if you're getting this and you made it this
you're getting this and you made it this far with doing this, you're perfectly
far with doing this, you're perfectly fine. I like being make sure we minimize
fine. I like being make sure we minimize our steps, right? So, I'm going to X out
our steps, right? So, I'm going to X out of this. I'm going to and this puts that
of this. I'm going to and this puts that salary hour adjusted back on the end.
salary hour adjusted back on the end. I'm going to drag reordered columns to
I'm going to drag reordered columns to the bottom. Now, whenever I take salary
the bottom. Now, whenever I take salary hour adjusted over here, it's going to
hour adjusted over here, it's going to insert it into that current step of
insert it into that current step of reorg. So, there's no duplicate of that.
reorg. So, there's no duplicate of that. So, you can feel free to move these
So, you can feel free to move these applied steps around to wherever you
applied steps around to wherever you need them to be. Um, but you need to be
need them to be. Um, but you need to be careful with how you do it. In this
careful with how you do it. In this case, right, I get an error message. the
case, right, I get an error message. the column salary hour average wasn't found
column salary hour average wasn't found because it's created in this step. So
because it's created in this step. So you need to make sure whenever you're
you need to make sure whenever you're moving things you are keeping them in an
moving things you are keeping them in an order that keeps track of the current
order that keeps track of the current columns. Anyway, let's go inspect this.
columns. Anyway, let's go inspect this. I'm going to close and apply and I'm
I'm going to close and apply and I'm going to create a new page. And in this
going to create a new page. And in this we're going to be making a clustered bar
we're going to be making a clustered bar chart. We want to compare this for the
chart. We want to compare this for the different job title shorts. So I'll drag
different job title shorts. So I'll drag that to the y ais. And now we can take
that to the y ais. And now we can take something like the salary year average
something like the salary year average to the x-axis. I want to aggregate this
to the x-axis. I want to aggregate this by a median and salary hour adjusted
by a median and salary hour adjusted also to the x-axis. This one will also
also to the x-axis. This one will also be median. And bam, what we can see from
be median. And bam, what we can see from this is well, let's go into focus mode
this is well, let's go into focus mode that consistently hourly salaries are
that consistently hourly salaries are consistently below yearly salaries. And
consistently below yearly salaries. And this is a great data point or a good
this is a great data point or a good insight because we need to understand or
insight because we need to understand or you want need to understand that yeah
you want need to understand that yeah you may be taking a job as hourly but
you may be taking a job as hourly but most likely you're going to get
most likely you're going to get underpaid somebody that's paying on a
underpaid somebody that's paying on a yearly basis which is kind of jacked up
yearly basis which is kind of jacked up and kind of pushes or trying to make
and kind of pushes or trying to make people get full-time jobs with salaries
people get full-time jobs with salaries vice somebody just working hourly. And
vice somebody just working hourly. And in the final file I put together this
in the final file I put together this scatter plot which I'm trying to show by
scatter plot which I'm trying to show by this. I made them the axises equal where
this. I made them the axises equal where this one the left side is the adjusted
this one the left side is the adjusted or sorry the y- axis is the adjusted
or sorry the y- axis is the adjusted salary and the x-axis is the yearly
salary and the x-axis is the yearly salary and these the axises goes from
salary and these the axises goes from 80,000 to 160,000 for both of these. So
80,000 to 160,000 for both of these. So the the actual area itself the plot area
the the actual area itself the plot area is similar across each. Anyway, what
is similar across each. Anyway, what we'd hope to see with this line of best
we'd hope to see with this line of best fit between all these different job
fit between all these different job titles right here is that it goes
titles right here is that it goes exactly splits in between the two.
exactly splits in between the two. Unfortunately, it's inclined or morely
Unfortunately, it's inclined or morely more towards the yearly median salary,
more towards the yearly median salary, which is also what we showed in this bar
which is also what we showed in this bar chart in that yearly salaries are higher
chart in that yearly salaries are higher than those adjusted hour salaries. All
than those adjusted hour salaries. All right, so you have some practice
right, so you have some practice problems now to go through and get more
problems now to go through and get more familiar with using the Power Query
familiar with using the Power Query Editor. In the next lesson, we're going
Editor. In the next lesson, we're going to be using the Power Query editor
to be using the Power Query editor specifically to bring in and clean up
specifically to bring in and clean up the data set that we're going to be
the data set that we're going to be using for the final project. All right,
using for the final project. All right, with that, I'll see you in the next one.
In this lesson, we're going to be importing in our final data set that
importing in our final data set that we're going to be using for our second
we're going to be using for our second project. It's quick to note there's no
project. It's quick to note there's no difference in data between the two.
difference in data between the two. We'll get to all that in a little bit,
We'll get to all that in a little bit, but it's more important if you
but it's more important if you understand there's not going to be
understand there's not going to be really a change in data, but in how we
really a change in data, but in how we can actually analyze it. Now, what do I
can actually analyze it. Now, what do I mean by this?
So, I'm inside the project file from the last lesson where we imported in our job
last lesson where we imported in our job postings flat CSV. And if I scroll on
postings flat CSV. And if I scroll on over here specifically to these two
over here specifically to these two columns on job skills and job type
columns on job skills and job type skills, we're going to focus on job
skills, we're going to focus on job skills for a time being. It is of the
skills for a time being. It is of the format text and it's a list of skills in
format text and it's a list of skills in here. But how the heck am I supposed to
here. But how the heck am I supposed to use this these skills when they're
use this these skills when they're associated with a certain job? Like you
associated with a certain job? Like you could have multiple skills to a job. If
could have multiple skills to a job. If I were try to create a bar chart of
I were try to create a bar chart of these skills and as as you expect if I
these skills and as as you expect if I try to drop something like the job
try to drop something like the job skills into here doing it by count going
skills into here doing it by count going into focus mode so we can see it better.
into focus mode so we can see it better. Basically it's just providing counts of
Basically it's just providing counts of these different lists but this doesn't
these different lists but this doesn't really provide us cuz the it hasn't
really provide us cuz the it hasn't broken up these skills. And remember
broken up these skills. And remember from this looking at the model view this
from this looking at the model view this is only one table that has everything in
is only one table that has everything in it. It's called a flat table. Well, here
it. It's called a flat table. Well, here I am in the final file for this lesson.
I am in the final file for this lesson. And in it, I'm an able to analyze what
And in it, I'm an able to analyze what are the top skills and data. Basically,
are the top skills and data. Basically, we're looking at those skills and
we're looking at those skills and they're actually broken out individually
they're actually broken out individually for this, but have the appropriate job
for this, but have the appropriate job count for how many jobs there are. How
count for how many jobs there are. How is this even possible? Well, if we go
is this even possible? Well, if we go into the model view for this final video
into the model view for this final video file of the lesson, we can see that we
file of the lesson, we can see that we have multiple tables inside of here and
have multiple tables inside of here and we have these lines between them
we have these lines between them allowing us to connect relationships to
allowing us to connect relationships to it. Now, we're going to get all into all
it. Now, we're going to get all into all this and break it down further, but the
this and break it down further, but the gist of it is is we have one table with
gist of it is is we have one table with all of our job postings and then one
all of our job postings and then one table with our skills and we're
table with our skills and we're connecting it to the two and we're able
connecting it to the two and we're able to query across these tables. So, let's
to query across these tables. So, let's break this concept down by looking at
break this concept down by looking at this erd or entity relationship diagram
this erd or entity relationship diagram of the final table of what we just saw
of the final table of what we just saw in PowerBI but broken out here. So for
in PowerBI but broken out here. So for this this is arranged into what's called
this this is arranged into what's called a star star schema and we have fact
a star star schema and we have fact tables and then dimensional tables
tables and then dimensional tables specifically we have our job postings
specifically we have our job postings fact table that's why facts at the end
fact table that's why facts at the end and then all these other ones are
and then all these other ones are dimensional table tables that's why we
dimensional table tables that's why we have the dim at the end this is a
have the dim at the end this is a shorthand notation and is pretty common
shorthand notation and is pretty common whenever you're using this type of
whenever you're using this type of structure on how you'd expect things to
structure on how you'd expect things to be named anyway the job posting fact
be named anyway the job posting fact table contains all the measurable data.
table contains all the measurable data. So, every single job posting, if you
So, every single job posting, if you worked in something like sales and had a
worked in something like sales and had a similar thing, all of the different
similar thing, all of the different orders would probably be in the fact
orders would probably be in the fact table and then things like information
table and then things like information on the customers or information on the
on the customers or information on the stores would be in the dimensional
stores would be in the dimensional tables. Similarly, our dimension tables
tables. Similarly, our dimension tables have things like the company and then
have things like the company and then also the skills. These fact tables are
also the skills. These fact tables are going to take much more rows because
going to take much more rows because they contain every single attribute.
they contain every single attribute. Whereas something like a company dim is
Whereas something like a company dim is only going to contain a company once or
only going to contain a company once or a skills dim is only going to contain a
a skills dim is only going to contain a skill once but then link it to the job.
skill once but then link it to the job. Now because we're using this fact and
Now because we're using this fact and dimensional tables, it's commonly
dimensional tables, it's commonly referred to as a star schema. Going back
referred to as a star schema. Going back to PowerBI, it's hard to really see star
to PowerBI, it's hard to really see star schema with this one because we only
schema with this one because we only have basically two relationships coming
have basically two relationships coming off of the skills in the company. But if
off of the skills in the company. But if we go to the very last lesson file,
we go to the very last lesson file, which we'll get to at the end of chapter
which we'll get to at the end of chapter 4, this starts to look more like a star
4, this starts to look more like a star schema because we have our job posting
schema because we have our job posting fact table and then we're going to
fact table and then we're going to create even more dimensional tables
create even more dimensional tables creating this star schema. But that's
creating this star schema. But that's for chapter four. Getting ahead of
for chapter four. Getting ahead of oursel. Now, this isn't to say flat
oursel. Now, this isn't to say flat tables are completely useless. Flat
tables are completely useless. Flat tables have their time and place,
tables have their time and place, especially for those that are maybe new
especially for those that are maybe new to analyzing data or aren't familiar
to analyzing data or aren't familiar with data set. It makes it have a simple
with data set. It makes it have a simple structure and super easy to actually
structure and super easy to actually query. But as we demonstrated with that
query. But as we demonstrated with that star schema in the final lesson for
star schema in the final lesson for this, right, we're going to be able to
this, right, we're going to be able to actually get in and do some deeper
actually get in and do some deeper analysis because now we can actually
analysis because now we can actually analyze multiple skills for a job
analyze multiple skills for a job posting and flat tables can't handle
posting and flat tables can't handle this. And so they're only they're
this. And so they're only they're somewhat limited if you will.
somewhat limited if you will. So enough yapping. Let's actually put
So enough yapping. Let's actually put this into practice and import in this
this into practice and import in this data set. And during this, we're going
data set. And during this, we're going to be diving into an important concept
to be diving into an important concept of reference first query. Anyway,
of reference first query. Anyway, starting off with a blank report for
starting off with a blank report for this. So, we have this file. Let's get
this. So, we have this file. Let's get into getting it. Specifically, we want
into getting it. Specifically, we want to get our data. As we learned
to get our data. As we learned previously, we can get it from a folder.
previously, we can get it from a folder. So, after selecting more, I navigate
So, after selecting more, I navigate into folder and select connect. And for
into folder and select connect. And for this, I'm going to select the location
this, I'm going to select the location of our star schema files. And this is
of our star schema files. And this is inside of our PowerBI data analytics
inside of our PowerBI data analytics course project folder underneath data.
course project folder underneath data. And in this folder called star schema
And in this folder called star schema files, we have four different CSV files
files, we have four different CSV files that we're going to be importing for
that we're going to be importing for this. Anyway, I've navigated to it. I'm
this. Anyway, I've navigated to it. I'm clicking okay. And similar before, this
clicking okay. And similar before, this is showing the four different files
is showing the four different files which is going to be made into the four
which is going to be made into the four different tables. We do not want to
different tables. We do not want to combine and transform data or combine
combine and transform data or combine and load. We don't want to do this
and load. We don't want to do this option. We need to go into the power
option. We need to go into the power query editor. So we're going to go to
query editor. So we're going to go to transform data. What we need to do now
transform data. What we need to do now inside of this power query editor is we
inside of this power query editor is we need to drill down or create queries for
need to drill down or create queries for each one of these. I can actually
each one of these. I can actually demonstrate this inside the star schema
demonstrate this inside the star schema files query. If I want to navigate to
files query. If I want to navigate to job postings fact, I can click binary
job postings fact, I can click binary and it basically does the entire cleanup
and it basically does the entire cleanup necessary to get this job postings fact
necessary to get this job postings fact table all ready to go. But the problem
table all ready to go. But the problem is now you know I'm lazy. I need to now
is now you know I'm lazy. I need to now do this for these three other sources. I
do this for these three other sources. I don't want to go through and actually
don't want to go through and actually select new source, do that again of we
select new source, do that again of we selecting the file and then uploading
selecting the file and then uploading again. I'm going to do something
again. I'm going to do something actually even simpler than that. So I'm
actually even simpler than that. So I'm going to remove these different steps
going to remove these different steps that we did right here up to the point
that we did right here up to the point of source. And this is getting into now
of source. And this is getting into now how we can create new queries. We can
how we can create new queries. We can either duplicate it and in this case
either duplicate it and in this case this duplicated one which has the
this duplicated one which has the parenthesis 2 just has the same files or
parenthesis 2 just has the same files or same code that if we look at the
same code that if we look at the previous query as that one that's
previous query as that one that's actually not showing much. So let's
actually not showing much. So let's actually instead I'm going to delete
actually instead I'm going to delete this one and with this star schema file
this one and with this star schema file I'm going to make some changes to it.
I'm going to make some changes to it. Specifically let's just say go into the
Specifically let's just say go into the job postings fact table. And now
job postings fact table. And now whenever I rightclick this one and
whenever I rightclick this one and select duplicate, notice all of these
select duplicate, notice all of these applied steps were done with this
applied steps were done with this whenever I duplicated this. However, if
whenever I duplicated this. However, if I were to rightclick this one and
I were to rightclick this one and instead click reference to create a new
instead click reference to create a new query number three, the reference one,
query number three, the reference one, this one only has one step. And the step
this one only has one step. And the step looking at it up here is hey set it
looking at it up here is hey set it equal to star schema files which is this
equal to star schema files which is this first query. So the point I'm trying to
first query. So the point I'm trying to make is with the duplicate you don't
make is with the duplicate you don't sometimes want to do this especially if
sometimes want to do this especially if it's going to just repeat all the steps
it's going to just repeat all the steps when they've been done already. It's
when they've been done already. It's going to cause a necessary load time
going to cause a necessary load time later on. So let's go ahead and delete
later on. So let's go ahead and delete both these and then from there remove
both these and then from there remove those steps to get into showing more
those steps to get into showing more steps necessary. And now for this, what
steps necessary. And now for this, what we're actually going to do, I'm going to
we're actually going to do, I'm going to rightclick this and I'm going to
rightclick this and I'm going to reference it. And this first one, I want
reference it. And this first one, I want to reference it to be the job postings
to reference it to be the job postings fact table, which I've changed the name
fact table, which I've changed the name up in the properties right here. This
up in the properties right here. This one, we're going to dive into here. And
one, we're going to dive into here. And now this has our necessary table. So
now this has our necessary table. So we'll need to do this again for all
we'll need to do this again for all these other tables. I'll start with
these other tables. I'll start with skills dim once again. We'll reference
skills dim once again. We'll reference it. We'll click into skills dim. And I
it. We'll click into skills dim. And I didn't rename it first, but that's fine.
didn't rename it first, but that's fine. And I can still go in and say skills
And I can still go in and say skills dim. All right, just need to do the
dim. All right, just need to do the remaining two now. So now we have all
remaining two now. So now we have all four of the tables in. We have our fact
four of the tables in. We have our fact table, our skills dimensional table,
table, our skills dimensional table, skills job dim, and our company dim.
skills job dim, and our company dim. We're going to go ahead now and click
We're going to go ahead now and click close and apply to get this into our
close and apply to get this into our PowerBI file. In the data pane, I can
PowerBI file. In the data pane, I can see all our four tables along with our
see all our four tables along with our star schema files. I can even go to the
star schema files. I can even go to the model view, which is the most important
model view, which is the most important for this. and rearranging this all so we
for this. and rearranging this all so we can see it a little bit better. We can
can see it a little bit better. We can see that it established the
see that it established the relationships necessary between here.
relationships necessary between here. Now, we're going to jump into
Now, we're going to jump into relationships here in a second. I first
relationships here in a second. I first want to focus on this this star schema
want to focus on this this star schema file. This isn't really necessary inside
file. This isn't really necessary inside of this area here. And specifically, I'm
of this area here. And specifically, I'm not going to need it inside of the
not going to need it inside of the canvas. I don't really want that. And if
canvas. I don't really want that. And if I were to share this with somebody, I
I were to share this with somebody, I wouldn't want somebody to have or to see
wouldn't want somebody to have or to see it. Now, I could do something like this
it. Now, I could do something like this and I could hide it, but this isn't
and I could hide it, but this isn't hiding it in the model view. It's only
hiding it in the model view. It's only hiding it here inside of the data view.
hiding it here inside of the data view. So, actually, I'm going to recommend not
So, actually, I'm going to recommend not even loading this table into PowerBI.
even loading this table into PowerBI. So, all we need to do is go back into
So, all we need to do is go back into Power Query editor by going to transform
Power Query editor by going to transform data and with this star schema file, I'm
data and with this star schema file, I'm going to rightclick it and look at this.
going to rightclick it and look at this. We have this that's checked right now.
We have this that's checked right now. Enable load. We're gonna click it and
Enable load. We're gonna click it and it's gonna say, "Hey, there's possible
it's gonna say, "Hey, there's possible possible data loss warning. Promise you
possible data loss warning. Promise you we're not going to lose any data." And
we're not going to lose any data." And the name went into italics. And now
the name went into italics. And now right clicking, we'd see enable load is
right clicking, we'd see enable load is no longer clicked next to it. So
no longer clicked next to it. So whenever I click close and apply and
whenever I click close and apply and navigate to the model view, it's not in
navigate to the model view, it's not in here. And it keeps things super simple
here. And it keeps things super simple for anybody that you may pass this file
for anybody that you may pass this file on to.
on to. All right, so let's now get into
All right, so let's now get into relationships. And I'm actually going to
relationships. And I'm actually going to assume PowerBI was smart enough in this
assume PowerBI was smart enough in this case to pick up these different these
case to pick up these different these three different relationships between
three different relationships between our tables. But I'm going to assume that
our tables. But I'm going to assume that maybe it didn't work for you. So what
maybe it didn't work for you. So what we're going to do is go ahead and delete
we're going to do is go ahead and delete all of these different relationships in
all of these different relationships in here by right-clicking on them,
here by right-clicking on them, selecting delete. Now let's recreate all
selecting delete. Now let's recreate all of these for the job posting fact table.
of these for the job posting fact table. I want to connect these. And we can see
I want to connect these. And we can see we have company ID. We want to connect
we have company ID. We want to connect it to company ID. So I just drag it to
it to company ID. So I just drag it to each other. And then this new
each other. And then this new relationship pop-up window comes up
relationship pop-up window comes up here. In it, it has the table selected,
here. In it, it has the table selected, which columns are they selected on, and
which columns are they selected on, and it automatically selects the cardality.
it automatically selects the cardality. And this describes how rows from one
And this describes how rows from one table correlate to another. In this
table correlate to another. In this case, it's saying many to one. In the
case, it's saying many to one. In the job postings fact table, we can see here
job postings fact table, we can see here just from this snippet here at the top,
just from this snippet here at the top, the company ID, there's many.
the company ID, there's many. Specifically, we have 1145 multiple
Specifically, we have 1145 multiple times. There are many values for the
times. There are many values for the company dim. There's one value. Even
company dim. There's one value. Even just looking at this snippet, there's
just looking at this snippet, there's only one unique value in here. It
only one unique value in here. It automatically figures this out. This is
automatically figures this out. This is not something you need to do. There's
not something you need to do. There's also cross filter direction, which we're
also cross filter direction, which we're going to get to towards the end of this
going to get to towards the end of this lesson. And always we want to make this
lesson. And always we want to make this relationship active. I'll go ahead and
relationship active. I'll go ahead and click save. Now the other way we could
click save. Now the other way we could create a relationship is okay let's say
create a relationship is okay let's say in this case I want to now connect our
in this case I want to now connect our skills tables now together specifically
skills tables now together specifically skills job dim has a job ID column so I
skills job dim has a job ID column so I know I can connect to this job ID I'm
know I can connect to this job ID I'm not going to drag it instead I'm going
not going to drag it instead I'm going to rightclick it and I'm going to go
to rightclick it and I'm going to go into manage relationship in this I'm
into manage relationship in this I'm going to select hey let's add a new
going to select hey let's add a new relationship and that similar window
relationship and that similar window that we saw before is going to show
that we saw before is going to show there I'm going to put job postings fact
there I'm going to put job postings fact up at the top and then skills job dim
up at the top and then skills job dim underneath it and it automatically
underneath it and it automatically picked up that job ID that these are the
picked up that job ID that these are the columns it's going to be related on. Now
columns it's going to be related on. Now somewhat similar to the last one instead
somewhat similar to the last one instead of being a many to one this one is going
of being a many to one this one is going to be a one to many. Specifically
to be a one to many. Specifically there's only going to be one unique job
there's only going to be one unique job ID in here but in our skills job dim
ID in here but in our skills job dim there's going to be many job IDs.
there's going to be many job IDs. Unfortunately we only have a data
Unfortunately we only have a data preview of three values. So, I can't
preview of three values. So, I can't show that. In fact, job ID five. There's
show that. In fact, job ID five. There's there's multiple values of five in
there's multiple values of five in there. Anyway, I'm going to click go
there. Anyway, I'm going to click go ahead and save because we're going to
ahead and save because we're going to keep everything else by default. And I'm
keep everything else by default. And I'm going to close out of this. And now we
going to close out of this. And now we can see that this relationship is going.
can see that this relationship is going. And when I highlight it over, we can see
And when I highlight it over, we can see that the job ID is there. All right.
that the job ID is there. All right. Let's just connect the last table. And
Let's just connect the last table. And that's going to be connecting the SC uh
that's going to be connecting the SC uh skills job dim down into the skills dim.
skills job dim down into the skills dim. Okay. In this case, we're once again
Okay. In this case, we're once again going to connect on a skill ID. This is
going to connect on a skill ID. This is a many to one relationship. Inside the
a many to one relationship. Inside the skills job dim table, there's many
skills job dim table, there's many values. In this case, multiple ones. But
values. In this case, multiple ones. But there's only one unique value inside the
there's only one unique value inside the skill dim. Basically, this table lists
skill dim. Basically, this table lists all the different skills in there, but
all the different skills in there, but only lists them once. I'm going to go
only lists them once. I'm going to go ahead and click okay. And now we have up
ahead and click okay. And now we have up all our relationships established. Now,
all our relationships established. Now, we can also see these relationships here
we can also see these relationships here with the nomenclature they're using.
with the nomenclature they're using. They have a one on this side and then an
They have a one on this side and then an asterisk here. So in this case from
asterisk here. So in this case from company dim to job posting facts it's a
company dim to job posting facts it's a one to many relationship. You're
one to many relationship. You're typically going to always see either a
typically going to always see either a one to many many to one or a one to one
one to many many to one or a one to one relationship. If you're getting to
relationship. If you're getting to situations of a many to many that's
situations of a many to many that's going to cause a lot of confusion and
going to cause a lot of confusion and it's going to eat up a lot of resources
it's going to eat up a lot of resources trying to match up data. Anyway that's
trying to match up data. Anyway that's beyond scope of this. That's more of an
beyond scope of this. That's more of an advanced technique to deal with. In most
advanced technique to deal with. In most cases, you're going to be seeing this
cases, you're going to be seeing this one to many or many to one. Anyway,
one to many or many to one. Anyway, let's get into verifying that this is
let's get into verifying that this is set up correctly by first visualizing
set up correctly by first visualizing the company table. So, we're going to
the company table. So, we're going to drag a stack bar chart into here. Going
drag a stack bar chart into here. Going to minimize the filter so we can see
to minimize the filter so we can see this a little bit better. Anyway, with
this a little bit better. Anyway, with our company DIM table that has the
our company DIM table that has the company information in it, such as
company information in it, such as company ID, links to the companies, the
company ID, links to the companies, the name of the company, I'm going to go
name of the company, I'm going to go ahead and drag that into the Yaxis. And
ahead and drag that into the Yaxis. And then inside of job postings fact, recall
then inside of job postings fact, recall that no, we no longer have the company
that no, we no longer have the company name inside of here. That's why we
name inside of here. That's why we dragged it from above. But also with
dragged it from above. But also with this, making this a little bit bigger.
this, making this a little bit bigger. We do have inside of here a job ID. So
We do have inside of here a job ID. So we can now start doing the job ID, the
we can now start doing the job ID, the count of the job ID vice doing that
count of the job ID vice doing that count of that job title short, which I
count of that job title short, which I feel a count of job ID is more common in
feel a count of job ID is more common in practice. Anyway, we can see that we're
practice. Anyway, we can see that we're using these multiple different tables
using these multiple different tables because we have these check marks here
because we have these check marks here saying we're using these tables. So,
saying we're using these tables. So, we're filtering across tables. And with
we're filtering across tables. And with this going into focus mode, we can now
this going into focus mode, we can now see the count of those different jobs, I
see the count of those different jobs, I mean companies. We could even take this
mean companies. We could even take this a step further by copying this and then
a step further by copying this and then pasting it. And instead of doing counts
pasting it. And instead of doing counts of jobs, we could drag that salary year
of jobs, we could drag that salary year average into here, adjust it to a median
average into here, adjust it to a median aggregation, and then see things like,
aggregation, and then see things like, hey, Goldman Tech Resourcing gives up to
hey, Goldman Tech Resourcing gives up to $870,000
$870,000 for a median salary. Not too bad. So,
for a median salary. Not too bad. So, that's the company information. Let's
that's the company information. Let's create a new page and analyze the skills
create a new page and analyze the skills or if we can analyze the skills. Now,
or if we can analyze the skills. Now, just to remember, right, this one's a
just to remember, right, this one's a little bit more complicated. We have a
little bit more complicated. We have a skills job dim and then a skills dim
skills job dim and then a skills dim table. Why do we have two? Well, going
table. Why do we have two? Well, going to the skills job dim table, we have our
to the skills job dim table, we have our job IDs and then our skill ID. I'm going
job IDs and then our skill ID. I'm going to sort the job ID in ascending order to
to sort the job ID in ascending order to better showcase this. But basically,
better showcase this. But basically, remember, we could have multiple
remember, we could have multiple different skills for a job. So, in this
different skills for a job. So, in this case, job ID of one has skill of 205 and
case, job ID of one has skill of 205 and 178. and then our skills dim table. We
178. and then our skills dim table. We could then inspect from here. Navigating
could then inspect from here. Navigating to 205, we could see, hey, the skill ID
to 205, we could see, hey, the skill ID is a skill ID of flow and that 178 is
is a skill ID of flow and that 178 is for Tableau, which is the type analyst
for Tableau, which is the type analyst tools. Anyway, you're probably like,
tools. Anyway, you're probably like, Luke, why the heck do you have multiple
Luke, why the heck do you have multiple tables in this case? Well, the reason is
tables in this case? Well, the reason is to solve an issue where there can be
to solve an issue where there can be multiple skills for a job. But for our
multiple skills for a job. But for our companies, there can't be multiple
companies, there can't be multiple companies listing the same job posting.
companies listing the same job posting. There's only one. So, in this case, we
There's only one. So, in this case, we were able to make it into only one
were able to make it into only one table. And we have one value or one
table. And we have one value or one company to many different job postings
company to many different job postings is put out. But we wouldn't be able to
is put out. But we wouldn't be able to do that with just a skills dim directly
do that with just a skills dim directly connected to this. Remember, we'd have a
connected to this. Remember, we'd have a many to many relationship. This would be
many to many relationship. This would be a mess. It'd be a heck to deal with.
a mess. It'd be a heck to deal with. That's why we have to have this
That's why we have to have this intermediate table skills job dim.
intermediate table skills job dim. Anyway, enough me yapping. Let's
Anyway, enough me yapping. Let's actually get into trying to visualize
actually get into trying to visualize this. Once again, we're going to insert
this. Once again, we're going to insert in a stack bar chart. We're going to use
in a stack bar chart. We're going to use the skills dim to insert in our skills
the skills dim to insert in our skills into the yaxis and then go to the job
into the yaxis and then go to the job postings fact table to put remember that
postings fact table to put remember that count of job ID. Now, if you notice by
count of job ID. Now, if you notice by this, we have relationship issues with
this, we have relationship issues with this. Mainly, all of these values, the
this. Mainly, all of these values, the count of the job ID is 470,000.
count of the job ID is 470,000. [Music]
[Music] Basically, the count of all the
Basically, the count of all the different job IDs. What's going on here?
different job IDs. What's going on here? Well, it deals with cross filter.
So, what's going on here? Well, let's navigate back to that model view. And
navigate back to that model view. And I'm going to move these around slightly.
I'm going to move these around slightly. specifically. I don't care about the
specifically. I don't care about the company dim table. Dragged it off the
company dim table. Dragged it off the screen for right now. We care about
screen for right now. We care about these skills tables. All right. So,
these skills tables. All right. So, what's going on here? And that has to
what's going on here? And that has to deal with this cross filter direction.
deal with this cross filter direction. Right now, if I were to double click on
Right now, if I were to double click on this, I can see cross filter direction
this, I can see cross filter direction is on single. And there's only one arrow
is on single. And there's only one arrow on there. And it shows it's going from
on there. And it shows it's going from the job postings fact table so to the SC
the job postings fact table so to the SC skills job dim. And then over here on
skills job dim. And then over here on the skills dim table, we can see that
the skills dim table, we can see that the direction is from skills dim to
the direction is from skills dim to skills job dim. This arrow is correlated
skills job dim. This arrow is correlated with the filter direction or the flow of
with the filter direction or the flow of how we want data to go. Right now for
how we want data to go. Right now for this visualization, we're using the job
this visualization, we're using the job ID of job postings fact and then skills
ID of job postings fact and then skills of skills dim. And so we're trying to
of skills dim. And so we're trying to filter from skills and get what the job
filter from skills and get what the job I the count of the job ID is over here.
I the count of the job ID is over here. And so if we had and we did a flow of
And so if we had and we did a flow of the arrow, yeah, we can go into this
the arrow, yeah, we can go into this table, but then when we try to go
table, but then when we try to go through this relationship, it's only in
through this relationship, it's only in the direction opposite to this. So you
the direction opposite to this. So you can't do it. But job ID is in here.
can't do it. But job ID is in here. Could we do it for that? Well, let's
Could we do it for that? Well, let's find out. We're going to duplicate this
find out. We're going to duplicate this table and instead of doing the count the
table and instead of doing the count the job ID from this job postings fact
job ID from this job postings fact table, like I said, we're going to do it
table, like I said, we're going to do it from the skills job dim table and throw
from the skills job dim table and throw it into here. And bam, this one does
it into here. And bam, this one does work and shows us the counts of this.
work and shows us the counts of this. But if you remember from our company
But if you remember from our company analysis, we not only were able to do a
analysis, we not only were able to do a count of the jobs, we were also able to
count of the jobs, we were also able to do the median salary. So it solves the
do the median salary. So it solves the problem of getting the count. But now if
problem of getting the count. But now if I wanted to use the actual salary year
I wanted to use the actual salary year average column to get the median, I
average column to get the median, I still can't do that. So this is not the
still can't do that. So this is not the solution we necessarily want to do or
solution we necessarily want to do or the most optimal. I'm going to go ahead
the most optimal. I'm going to go ahead and remove this. What we can do instead
and remove this. What we can do instead to make sure that we get this filtering
to make sure that we get this filtering of skills to be able to happen all the
of skills to be able to happen all the way back to the job postings fact is I'm
way back to the job postings fact is I'm going to take this and rightclick it. Go
going to take this and rightclick it. Go to properties and for between these two
to properties and for between these two tables of job postings fact and skills
tables of job postings fact and skills job dim I'm going to change the cross
job dim I'm going to change the cross filter direction to both it ungrade this
filter direction to both it ungrade this area of apply security filter in both
area of apply security filter in both directions. We're not going to be
directions. We're not going to be applying security filters for this. I'm
applying security filters for this. I'm not controlling who has access to this
not controlling who has access to this data. Anybody can have access to it.
data. Anybody can have access to it. It's public so I don't care about that.
It's public so I don't care about that. Click save. So it updated here as that
Click save. So it updated here as that double arrow. Now when I go into report
double arrow. Now when I go into report view, bam, it is updated. And I can even
view, bam, it is updated. And I can even do something similar crl +v. Instead of
do something similar crl +v. Instead of doing that count of the job ID, I can
doing that count of the job ID, I can drag in that salary year average and do
drag in that salary year average and do that median value. And then we can see
that median value. And then we can see something like unreal has a median
something like unreal has a median salary of almost $101,000.
salary of almost $101,000. It looks like a lot more less frequent
It looks like a lot more less frequent skills have these higher salaries.
skills have these higher salaries. Basically, we can filter this for the
Basically, we can filter this for the top. We'll say top 20 skills. So, I'm
top. We'll say top 20 skills. So, I'm going to go to the skills filter. Do a
going to go to the skills filter. Do a top N. And we're going to do a count by
top N. And we're going to do a count by count of job ID. Selecting the top 20
count of job ID. Selecting the top 20 values. Go apply filter. And now,
values. Go apply filter. And now, closing this on out. We can see these
closing this on out. We can see these are the top 20 values. We can see
are the top 20 values. We can see something that's actually more useful
something that's actually more useful like Scala Spar, Kafka, and then we can
like Scala Spar, Kafka, and then we can even see data analytical tools down
even see data analytical tools down here. Even PowerBI makes the list.
here. Even PowerBI makes the list. Although second from last but at least
Although second from last but at least above Excel. So anytime you're working
above Excel. So anytime you're working with these fact and dimensional tables,
with these fact and dimensional tables, it's important to understand what is
it's important to understand what is going on with the filtering direction.
going on with the filtering direction. In the case of our company thing, we
In the case of our company thing, we were able to do that our company
were able to do that our company analysis because the company when we
analysis because the company when we selected the name here, we were able to
selected the name here, we were able to filter back into the job postings fact
filter back into the job postings fact table to get the count of that job ID.
table to get the count of that job ID. Now there's no practice problems for
Now there's no practice problems for this lesson. So congratulations. I do
this lesson. So congratulations. I do want you to make sure that you do
want you to make sure that you do understand what's going on with this
understand what's going on with this cross filtering and also relationships.
cross filtering and also relationships. So if you need to feel free to go back
So if you need to feel free to go back and rework any of this. We will be
and rework any of this. We will be testing these concepts in upcoming
testing these concepts in upcoming problems in the next lessons, but like I
problems in the next lessons, but like I said, none for this lesson. All right,
said, none for this lesson. All right, with that, I'll see you in the next
with that, I'll see you in the next lesson where we're going into advanced
lesson where we're going into advanced transformations. See you there.
Welcome to this lesson. We're going to be diving in deeper into using advanced
be diving in deeper into using advanced transformations to make that data set we
transformations to make that data set we just imported in for project 2 even more
just imported in for project 2 even more usable. Now, don't get too nervous that
usable. Now, don't get too nervous that the fact that the name of this is
the fact that the name of this is advanced transformations. It's well
advanced transformations. It's well within your capabilities. Let's take a
within your capabilities. Let's take a look at what we're going to do. In the
look at what we're going to do. In the last lesson we imported in, we went
last lesson we imported in, we went through and we were able to visualize
through and we were able to visualize based on the different skills what were
based on the different skills what were their counts. But if you have bosses or
their counts. But if you have bosses or stakeholders like me that are super
stakeholders like me that are super picky, they're not going to really like
picky, they're not going to really like that all these skills are lowercase and
that all these skills are lowercase and don't have the proper capitalization.
don't have the proper capitalization. Well, navigating to the lesson file that
Well, navigating to the lesson file that we're going to be completing by the end
we're going to be completing by the end of this and we're going to be have it
of this and we're going to be have it where the column for skills are going to
where the column for skills are going to be nice and cleaned up with all the
be nice and cleaned up with all the proper capitalization as necessary so we
proper capitalization as necessary so we have no complaining boss or
have no complaining boss or stakeholders. This is going to be done
stakeholders. This is going to be done using some basic text cleanup, a lot of
using some basic text cleanup, a lot of which we've seen before, but also a new
which we've seen before, but also a new concept of conditional columns,
concept of conditional columns, basically an if statement. Now, the
basically an if statement. Now, the first thing that we're actually going to
first thing that we're actually going to be cleaning up revolves around this job
be cleaning up revolves around this job schedule type column, which is inside of
schedule type column, which is inside of our job postings fact table. If we go
our job postings fact table. If we go and click this drop- down arrow here, we
and click this drop- down arrow here, we can see that there is multiple different
can see that there is multiple different values. And this makes it very difficult
values. And this makes it very difficult to say like, hey, what happens if I want
to say like, hey, what happens if I want to analyze a job that has part-time and
to analyze a job that has part-time and contractor? Why can't I make it to where
contractor? Why can't I make it to where the job is part-time and contractor?
the job is part-time and contractor? Previously, in the past, we've just gone
Previously, in the past, we've just gone through and analyzed this by unselecting
through and analyzed this by unselecting this and then only selecting the
this and then only selecting the keywords of like contractor, full-time,
keywords of like contractor, full-time, internship, part-time, and whatnot. But
internship, part-time, and whatnot. But unfortunately, that leaves out a lot of
unfortunately, that leaves out a lot of different jobs. So, we're going to clean
different jobs. So, we're going to clean up this column. Specifically, what we're
up this column. Specifically, what we're going to be doing, we go into the final
going to be doing, we go into the final file for this lesson. We're going to be
file for this lesson. We're going to be creating another dimensional table. And
creating another dimensional table. And this is going to have the job schedule
this is going to have the job schedule type in it. and it's going to be
type in it. and it's going to be connected to our job postings fact table
connected to our job postings fact table via a job ID. If I navigate into table
via a job ID. If I navigate into table view and check out this schedule dim,
view and check out this schedule dim, what I can see is that it's going to
what I can see is that it's going to have an associated job ID and then the
have an associated job ID and then the second column is going to be the uh the
second column is going to be the uh the job schedule type. If I sort this job ID
job schedule type. If I sort this job ID in ascending order, we can see things
in ascending order, we can see things like the job ID zero has multiple
like the job ID zero has multiple different conditions that meets it. So
different conditions that meets it. So now, similar to how jobs can have
now, similar to how jobs can have multiple skills, we can also have it to
multiple skills, we can also have it to where jobs have multiple job schedule
where jobs have multiple job schedule types. With this, we'll be able now to
types. With this, we'll be able now to analyze not only different job counts or
analyze not only different job counts or the correct job counts for a specific uh
the correct job counts for a specific uh job type, but also things like this, the
job type, but also things like this, the median median yearly salary of different
median median yearly salary of different job types. All right, enough meapping.
job types. All right, enough meapping. Let's jump into creating this table
Let's jump into creating this table where we have these two columns, and
where we have these two columns, and it's specific to the job schedule type.
So for this, feel free to start with the file that we were using at the end of
file that we were using at the end of last lesson. If you lost track along the
last lesson. If you lost track along the way, you can just jump into the previous
way, you can just jump into the previous lessons file of 3.3 project 2 import.
lessons file of 3.3 project 2 import. Right now in here under the model view,
Right now in here under the model view, I'm going to go ahead and close these
I'm going to go ahead and close these tabs. We only have dimensional tables
tabs. We only have dimensional tables regarding the skills and the company
regarding the skills and the company down. Like I said, we want to create one
down. Like I said, we want to create one for the schedule type. And the schedule
for the schedule type. And the schedule type information is inside of this job
type information is inside of this job postings fact table. So we need to get
postings fact table. So we need to get it out of there into its own table. So
it out of there into its own table. So I'm going go into transform data.
I'm going go into transform data. Transform data in order to open Power
Transform data in order to open Power Query Editor. So we're going to want to
Query Editor. So we're going to want to be cleaning up this job schedule type
be cleaning up this job schedule type column which is in that job postings
column which is in that job postings fact, right? Which is right here. So the
fact, right? Which is right here. So the first thing we need to do in order to
first thing we need to do in order to get our own dimensional table is we want
get our own dimensional table is we want to create a new table with well one job
to create a new table with well one job schedule type and then also the job ID.
schedule type and then also the job ID. Remember going to that final table this
Remember going to that final table this is what we want it to look like. So with
is what we want it to look like. So with this we need to either we can rightclick
this we need to either we can rightclick it and see we can either duplicate or
it and see we can either duplicate or reference. Now you can also access this
reference. Now you can also access this by ensuring job postings facts is
by ensuring job postings facts is selected and then under the home tab
selected and then under the home tab going to manage your queries. In this
going to manage your queries. In this case I can delete it, duplicate it or
case I can delete it, duplicate it or reference. Remember duplicate as I just
reference. Remember duplicate as I just did now keeps all those same steps going
did now keeps all those same steps going on. I don't want to add unnecessary
on. I don't want to add unnecessary steps and increase the load time. So
steps and increase the load time. So we're not going to do this one. I'm
we're not going to do this one. I'm going to select this one, go to manage,
going to select this one, go to manage, and delete it. Instead, we're going to
and delete it. Instead, we're going to select this one. And now we're going to
select this one. And now we're going to manage it and reference it. And as we
manage it and reference it. And as we can see the source for this step is only
can see the source for this step is only job postings fact which relates to this
job postings fact which relates to this table right here which has those
table right here which has those multiple different steps in it. And as a
multiple different steps in it. And as a quick refresher you can for this table
quick refresher you can for this table just to verify the steps you can do
just to verify the steps you can do something underneath the home tab going
something underneath the home tab going into the advanced editor and this has
into the advanced editor and this has all the code necessary to build this
all the code necessary to build this table which is only a few lines of code.
table which is only a few lines of code. Anyway, cool story. Let's rename this.
Anyway, cool story. Let's rename this. Now up here, we'll name it to schedule
Now up here, we'll name it to schedule dim. On renaming it, press enter and
dim. On renaming it, press enter and everything updates for it.
everything updates for it. So with this table, we now want to keep
So with this table, we now want to keep just two columns. Job ID and job
just two columns. Job ID and job schedule type. Now what we could do is
schedule type. Now what we could do is we come to the very last column here
we come to the very last column here underneath the home tab. I can go to
underneath the home tab. I can go to remove columns. And they have this first
remove columns. And they have this first one of columns. So I can select remove
one of columns. So I can select remove it. And then I can just keep on doing
it. And then I can just keep on doing this until all the different columns are
this until all the different columns are removed and that would take a while. So
removed and that would take a while. So I'm actually going to remove this step
I'm actually going to remove this step of remove columns. We're going to do a
of remove columns. We're going to do a better approach and instead we're going
better approach and instead we're going to select the two columns we want. I'm
to select the two columns we want. I'm going to select this one. Scroll on over
going to select this one. Scroll on over to job schedule type. Holding control
to job schedule type. Holding control I'm going to press job schedule type. So
I'm going to press job schedule type. So now both of these are now selected. And
now both of these are now selected. And then I can go to remove other columns.
then I can go to remove other columns. Now the other method we could do this
Now the other method we could do this that's also just as easy is I can remove
that's also just as easy is I can remove that step again and in this case I could
that step again and in this case I could just doesn't we don't have to have any
just doesn't we don't have to have any column specific column selected. I could
column specific column selected. I could go to choose column and then select
go to choose column and then select choose columns and then from now we
choose columns and then from now we select the columns we want. We want job
select the columns we want. We want job ID and job schedule type. This is
ID and job schedule type. This is actually probably the easiest way and it
actually probably the easiest way and it eventually ends up using just that
eventually ends up using just that removed other column step. So
removed other column step. So remembering our end goal, we want to
remembering our end goal, we want to create only one schedule type per row.
create only one schedule type per row. If I just open this up here to select or
If I just open this up here to select or in view inside of here, I can see that
in view inside of here, I can see that we have multiple different values for
we have multiple different values for these. Also, you may notice this in many
these. Also, you may notice this in many of these different lists that it says
of these different lists that it says list is incomplete. All you have to do
list is incomplete. All you have to do is load more and then you get all the
is load more and then you get all the list of all the different options in
list of all the different options in there. Remember, this is due to the fact
there. Remember, this is due to the fact that we're doing column profiling based
that we're doing column profiling based on that top thousand rows. So whenever I
on that top thousand rows. So whenever I do the drop down like this, it's only
do the drop down like this, it's only showing the values or the unique values
showing the values or the unique values for the first thousand rows. Anyway,
for the first thousand rows. Anyway, well, we need to get a game plan
well, we need to get a game plan together on how we're going to create
together on how we're going to create these into different rows. My idea is
these into different rows. My idea is this. We're going to be using the comma
this. We're going to be using the comma within these fields in order to split
within these fields in order to split them into new rows. Specifically, I can
them into new rows. Specifically, I can select job schedule type. This is what
select job schedule type. This is what we're skipping some steps right now. I
we're skipping some steps right now. I just want to show this. We're going to
just want to show this. We're going to go into split column by delimiter and I
go into split column by delimiter and I can specify that we're going to be
can specify that we're going to be splitting by comma and each occurrence
splitting by comma and each occurrence of the delimiter itself and other
of the delimiter itself and other advanced options we're going to be doing
advanced options we're going to be doing rows. Now the problem with this is as
rows. Now the problem with this is as you're going to see like this case where
you're going to see like this case where we have an and value it didn't split it
we have an and value it didn't split it as necessary and we'd have to do it
as necessary and we'd have to do it again. Also just popping out this
again. Also just popping out this dropdown here. We can see that we have
dropdown here. We can see that we have like oh this one has and in this this is
like oh this one has and in this this is just I'm not liking I'm not liking how
just I'm not liking I'm not liking how this is done. So here's my
this is done. So here's my recommendation. Let's actually go ahead
recommendation. Let's actually go ahead and remove this change type and this
and remove this change type and this split column by delimiter and let's go
split column by delimiter and let's go forth with replacing
forth with replacing like in this case let's replace this
like in this case let's replace this value right here with a comma. So under
value right here with a comma. So under transform I can select this column and
transform I can select this column and we can go to replace values and for this
we can go to replace values and for this for the value to find we're going to do
for the value to find we're going to do space and it is going to be able to pick
space and it is going to be able to pick up this space and we want to replace
up this space and we want to replace this with a comma and then go ahead and
this with a comma and then go ahead and click okay. All right not bad. We can
click okay. All right not bad. We can inspect these values and we can see that
inspect these values and we can see that in the cases where there was multiple
in the cases where there was multiple like three it replaced that and but now
like three it replaced that and but now it has two commas in there. So what I'm
it has two commas in there. So what I'm going to recommend instead is we're
going to recommend instead is we're going to go back one step to remove
going to go back one step to remove other columns and let's start by
other columns and let's start by actually replacing this portion
actually replacing this portion specifically. I'm going to click on it
specifically. I'm going to click on it so we can see it. Let's go forth with
so we can see it. Let's go forth with replacing this section of a comma space
replacing this section of a comma space and with just a comma before we do our
and with just a comma before we do our next one. So, making sure that I am on
next one. So, making sure that I am on that second step, I'm going to go to
that second step, I'm going to go to replace values. It asks if I want to
replace values. It asks if I want to insert a step. I do. I have this value
insert a step. I do. I have this value selected, so it automatically put in
selected, so it automatically put in there. I don't want it. What I want is
there. I don't want it. What I want is comma space and and we're going to
comma space and and we're going to replace it with a comma and then go.
replace it with a comma and then go. Okay. Okay. So, that step did it just
Okay. Okay. So, that step did it just fine, right? It's looking good. And then
fine, right? It's looking good. And then we have our next replace values. And
we have our next replace values. And that one replaces the commas in the just
that one replaces the commas in the just and alone. And I can just inspect this
and alone. And I can just inspect this by looking inside of here. Looking
by looking inside of here. Looking pretty good. And now I can use this
pretty good. And now I can use this split column. And specifically we want
split column. And specifically we want we can split by a number of different
we can split by a number of different things, number of characters, positions,
things, number of characters, positions, whatnot. We're going to be doing it by
whatnot. We're going to be doing it by delimiter because a comma is a
delimiter because a comma is a delimiter. So we're going to select or
delimiter. So we're going to select or enter that comma. You can do leftmost,
enter that comma. You can do leftmost, rightmost, or each occurrence, right? We
rightmost, or each occurrence, right? We could have multiple different values. So
could have multiple different values. So we want each occurrence. And for this,
we want each occurrence. And for this, we want to go into rows. We want to put
we want to go into rows. We want to put it underneath each other uh uh
it underneath each other uh uh underneath itself. We're actually going
underneath itself. We're actually going to demonstrate columns after this, but
to demonstrate columns after this, but for the time being, this is actually
for the time being, this is actually what is our solution going to be. So
what is our solution going to be. So we're going to click okay. And bam. Not
we're going to click okay. And bam. Not too bad. We have Well, let's actually
too bad. We have Well, let's actually inspect it. go to uh go to view and then
inspect it. go to uh go to view and then column profile. Look at this. We have
column profile. Look at this. We have these multiple different values in here.
these multiple different values in here. But if you look at it, some of these
But if you look at it, some of these like we have internship twice and we
like we have internship twice and we also have temp work twice and contractor
also have temp work twice and contractor twice. Why is that? Well, the issue
twice. Why is that? Well, the issue resolves in if I select something like
resolves in if I select something like part-time, I can see this right with
part-time, I can see this right with part-time there's actually an empty
part-time there's actually an empty space right before this. Not a big deal.
space right before this. Not a big deal. This is really easy to clean up
This is really easy to clean up underneath transform. We're going to go
underneath transform. We're going to go into once again text columns format and
into once again text columns format and we want to trim this trim these values.
we want to trim this trim these values. Basically remove any white space on the
Basically remove any white space on the left or right hand side. Now when we go
left or right hand side. Now when we go in to look at this column profile,
in to look at this column profile, there's only six unique values. I can
there's only six unique values. I can actually do the entire data set. And
actually do the entire data set. And looking at everything, there's actually
looking at everything, there's actually one additional this one of volunteer.
one additional this one of volunteer. And it looks like it's uh very minuscule
And it looks like it's uh very minuscule compared to all the rest. But at least
compared to all the rest. But at least with this we confirm we have just unique
with this we confirm we have just unique values. Now this is the final form of
values. Now this is the final form of our dimensional table. Everything is
our dimensional table. Everything is good to go.
good to go. Now I do want to quickly demonstrate
Now I do want to quickly demonstrate splitting columns. We split columns into
splitting columns. We split columns into rows. We're going to split into columns.
rows. We're going to split into columns. This by no means is necessary for you to
This by no means is necessary for you to do. I just want you to have an
do. I just want you to have an understanding that there are different
understanding that there are different options to actually split columns. So,
options to actually split columns. So, I'm going to remove these last few
I'm going to remove these last few steps. If you don't feel comfortable
steps. If you don't feel comfortable following along with this, don't feel uh
following along with this, don't feel uh feel like you're necessary to anyway.
feel like you're necessary to anyway. We're going to go back to the step where
We're going to go back to the step where we've had it necess or have it set up
we've had it necess or have it set up properly where the commas for all the
properly where the commas for all the different values are in the right
different values are in the right spaces. Also, it's doing column profile
spaces. Also, it's doing column profile on the entire data set. I'm just going
on the entire data set. I'm just going to check this back to 1,00 rows. That
to check this back to 1,00 rows. That way, it loads a little bit quicker.
way, it loads a little bit quicker. Anyway, underneath the home tab, we're
Anyway, underneath the home tab, we're going to split column. Once again, we're
going to split column. Once again, we're going to split by delimiter. Remember we
going to split by delimiter. Remember we did this by a comma and we did each
did this by a comma and we did each occurrence. Now under advanced options,
occurrence. Now under advanced options, it's actually selected by default to be
it's actually selected by default to be a column and the number of columns to
a column and the number of columns to split into is set. They put it in here
split into is set. They put it in here of three because looking at those three
of three because looking at those three rows, that's what it assumes it needs to
rows, that's what it assumes it needs to be. I mean, looking at those a thousand
be. I mean, looking at those a thousand rows, it looks like there's only three
rows, it looks like there's only three values at max or three commas at max. So
values at max or three commas at max. So that's why it has the suggestion of
that's why it has the suggestion of three. Anyway, let's go ahead and split
three. Anyway, let's go ahead and split this way. And what we can see is okay
this way. And what we can see is okay job zero has three values whereas job
job zero has three values whereas job one has only one value and then null for
one has only one value and then null for the rest. This is still technically
the rest. This is still technically usable. We just have to unpivot the
usable. We just have to unpivot the data. If I go underneath the transform
data. If I go underneath the transform tab and select underneath here, I can
tab and select underneath here, I can hear see here that we have unpivot
hear see here that we have unpivot columns which with the popup that it
columns which with the popup that it comes it says it translates all but the
comes it says it translates all but the currently unselected columns into
currently unselected columns into attribute and value pairs. Now we have
attribute and value pairs. Now we have job ID selected. So we actually want the
job ID selected. So we actually want the opposite unpivot other columns.
opposite unpivot other columns. Translate all but the currently selected
Translate all but the currently selected columns into attribute value pairs. And
columns into attribute value pairs. And what does it mean by attribute value
what does it mean by attribute value pairs? Well, let's look at it. Inside of
pairs? Well, let's look at it. Inside of here, we have our values, which are the
here, we have our values, which are the different job schedule types now. And
different job schedule types now. And the attribute was that former column
the attribute was that former column name, which I can go back into split
name, which I can go back into split column delimiter. These were the
column delimiter. These were the different column names. They are now
different column names. They are now underneath the attribute. So remember,
underneath the attribute. So remember, we only want to have two columns for
we only want to have two columns for ours. I can select this, go into home,
ours. I can select this, go into home, go to remove this column, and then under
go to remove this column, and then under the value, remember we don't want that
the value, remember we don't want that name. We could change it to job schedule
name. We could change it to job schedule type. And then I can see just looking at
type. And then I can see just looking at part-time that there is a white space
part-time that there is a white space before and after this. So going into
before and after this. So going into transform, I can go into format and
transform, I can go into format and trim. And now we have it in the same
trim. And now we have it in the same manner that we had it previously,
manner that we had it previously, although we had to do a heck of a lot
although we had to do a heck of a lot more different steps. I wanted to cover
more different steps. I wanted to cover that mainly for the aspect of the
that mainly for the aspect of the unpivot columns as you may receive data
unpivot columns as you may receive data in this format right here basically in a
in this format right here basically in a pivot table format and you'll need to
pivot table format and you'll need to unpivot it in order to get it into this
unpivot it in order to get it into this format. So pivoting and unpivoting is a
format. So pivoting and unpivoting is a super useful technique to know about.
super useful technique to know about. Anyway, I'm going to remove all these
Anyway, I'm going to remove all these steps, split the column by delimiter,
steps, split the column by delimiter, specifying it's a comma, and then we're
specifying it's a comma, and then we're going into rows, and then formatting
going into rows, and then formatting this comma to actually or formatting
this comma to actually or formatting this column to trim up the white space.
this column to trim up the white space. We'll leave it like this cuz this one
We'll leave it like this cuz this one easier. This is good to go. Let's close
easier. This is good to go. Let's close and load it in to analyze it.
That's pretty cool. Once we loaded it in, schedule dim the dimensional table
in, schedule dim the dimensional table automatically created a relationship to
automatically created a relationship to job postings fact. If it didn't do this,
job postings fact. If it didn't do this, I can delete this relationship and just
I can delete this relationship and just drag job ID over to here. Ensure that
drag job ID over to here. Ensure that it's selected to connect between these
it's selected to connect between these two. It's a many to one relationship.
two. It's a many to one relationship. Maintaining it single for now. #spoiler
Maintaining it single for now. #spoiler alert. And bam. So, let's get into
alert. And bam. So, let's get into analyzing this. I'm going to create a
analyzing this. I'm going to create a new page. And let's start off simple. We
new page. And let's start off simple. We just want to analyze the count of the
just want to analyze the count of the different job schedule types. So, I'm
different job schedule types. So, I'm going to drag from the SC schedule dim
going to drag from the SC schedule dim the job schedule type into the Y-axis.
the job schedule type into the Y-axis. And then from the job posting fact
And then from the job posting fact table, we want to count that job ID for
table, we want to count that job ID for all those unique job postings and get a
all those unique job postings and get a count. Now going into focus mode, we're
count. Now going into focus mode, we're going to see there's a problem with this
going to see there's a problem with this that we noticed before that we may have
that we noticed before that we may have noticed before. Well, it's actually two
noticed before. Well, it's actually two problems with this. First of all,
problems with this. First of all, there's blank values, null values in
there's blank values, null values in here. I don't like that. The second is
here. I don't like that. The second is that look at the counts of this for
that look at the counts of this for contractor. It's 478,000. Basically,
contractor. It's 478,000. Basically, every single row is being attributed to
every single row is being attributed to that. Why is that? Well, let's inspect
that. Why is that? Well, let's inspect from the model view. Remember schedule
from the model view. Remember schedule dim, we're using job schedule type and
dim, we're using job schedule type and we're trying to filter in the direction
we're trying to filter in the direction of the job ID. Right now, look at where
of the job ID. Right now, look at where this arrow is point. It's pointing
this arrow is point. It's pointing towards the schedule dim. So, it's
towards the schedule dim. So, it's preventing us from actually filtering in
preventing us from actually filtering in the direction we need to filter to get
the direction we need to filter to get the count from this table. So, how do we
the count from this table. So, how do we fix this? Well, we can rightclick it, go
fix this? Well, we can rightclick it, go to the properties, and we can change
to the properties, and we can change this cross filter direction right from
this cross filter direction right from single to both to where now once we save
single to both to where now once we save it, we can see that job schedule type
it, we can see that job schedule type should be allowed to filter the job ID
should be allowed to filter the job ID in this direction. Now, going back to
in this direction. Now, going back to report view, it is looking good. The
report view, it is looking good. The only thing I do not like with this is
only thing I do not like with this is this null value. Now, I could go apply a
this null value. Now, I could go apply a filter and remove job, uh, remove this
filter and remove job, uh, remove this blank value right here, but I'm going to
blank value right here, but I'm going to have to do that for every time I make a
have to do that for every time I make a visualization with this. Instead, the
visualization with this. Instead, the best bet to do is go back into Power
best bet to do is go back into Power Query and looking at that schedule dim,
Query and looking at that schedule dim, we want to remove the blanks. Now, I
we want to remove the blanks. Now, I will caution on this cuz this may be an
will caution on this cuz this may be an approach you may try to take. You can
approach you may try to take. You can select remove rows and they have this of
select remove rows and they have this of remove duplicates, remove blank rows and
remove duplicates, remove blank rows and remove errors. So in our case, let's try
remove errors. So in our case, let's try to remove blank rows. Well, whenever I
to remove blank rows. Well, whenever I go here and select this down arrow, I
go here and select this down arrow, I still have blank values in there. So
still have blank values in there. So technically, it's not filtering for the
technically, it's not filtering for the type of blank values that are located
type of blank values that are located inside of here that are actually
inside of here that are actually technically null values. Anyway, I'm
technically null values. Anyway, I'm going to remove this step of remove
going to remove this step of remove blank rows because it didn't work
blank rows because it didn't work anyway. And the best way to filter for
anyway. And the best way to filter for this is just uncheck blank inside of
this is just uncheck blank inside of here and then click okay. And it adds a
here and then click okay. And it adds a step for filtered rows to remove this.
step for filtered rows to remove this. Also, we can see that this green bar now
Also, we can see that this green bar now takes up the entire length of this. So,
takes up the entire length of this. So, I know it worked fine. Click close and
I know it worked fine. Click close and apply. Once it loads in the data, boom,
apply. Once it loads in the data, boom, it removes that blank value. So, now we
it removes that blank value. So, now we can do something like this. Since both
can do something like this. Since both of these are set up, instead of just
of these are set up, instead of just doing job count, we can also do the
doing job count, we can also do the median salary, changing this to median.
median salary, changing this to median. And we can see things like, oo,
And we can see things like, oo, part-time pays better than full-time.
part-time pays better than full-time. So, that's another unique thing that we
So, that's another unique thing that we found out about this. Not only do yearly
found out about this. Not only do yearly salary jobs pay better than hoursly, but
salary jobs pay better than hoursly, but part-time jobs are paying better than
part-time jobs are paying better than full-time jobs.
Let's get into the second portion of this, which should be a little bit
this, which should be a little bit quicker. We're going to go into focus
quicker. We're going to go into focus mode. Remember, we're trying to clean up
mode. Remember, we're trying to clean up now, as we demonstrated earlier, what
now, as we demonstrated earlier, what are the top skills and data,
are the top skills and data, specifically those different skills. We
specifically those different skills. We want to add the proper capitalization
want to add the proper capitalization for each of these as necessary. This
for each of these as necessary. This however is going to take a little bit
however is going to take a little bit more cleanup because if we navigate to
more cleanup because if we navigate to our final file we can see that yeah some
our final file we can see that yeah some of them do just start with only one
of them do just start with only one capital letter like Python but then you
capital letter like Python but then you have things like SQL and AWS which are
have things like SQL and AWS which are all capitals letters or you even have
all capitals letters or you even have something like PowerBI where the last
something like PowerBI where the last two letters are all capital letters.
two letters are all capital letters. Anyway, back in our file where we want
Anyway, back in our file where we want to actually modify this. Let's jump into
to actually modify this. Let's jump into cleaning this up. We're going to be
cleaning this up. We're going to be cleaning up specifically the skills dim
cleaning up specifically the skills dim table and this skills column right here.
table and this skills column right here. So, as we've seen before underneath the
So, as we've seen before underneath the transform tab, we have the option to
transform tab, we have the option to format different values. In this case,
format different values. In this case, text values. We could make our skills
text values. We could make our skills all lowercase, which they all are, or we
all lowercase, which they all are, or we can make it all uppercase in this case,
can make it all uppercase in this case, or we can even capitalize each word,
or we can even capitalize each word, which is actually what we want to do for
which is actually what we want to do for the first step. So, I'm going to go
the first step. So, I'm going to go ahead and remove this uppercase text one
ahead and remove this uppercase text one cuz we're not going to keep that one.
cuz we're not going to keep that one. All right. So, that's a good first step.
All right. So, that's a good first step. But now, if we look at values like SQL,
But now, if we look at values like SQL, it's not proper. We would expect to be
it's not proper. We would expect to be all caps for SQL. And there's only a
all caps for SQL. And there's only a handful of other names in here that I
handful of other names in here that I actually do want to clean up, such as
actually do want to clean up, such as NoSQL, PowerBI, DAX, of course, DAX, and
NoSQL, PowerBI, DAX, of course, DAX, and we'll give some love to SAS. So let's
we'll give some love to SAS. So let's just start with PowerBI first. We're
just start with PowerBI first. We're going to be using a conditional column.
going to be using a conditional column. Unfortunately, there's nothing under
Unfortunately, there's nothing under transform for this. So we have to add a
transform for this. So we have to add a new column. And we can come up here into
new column. And we can come up here into conditional column. Our current column
conditional column. Our current column is called skills. So we'll say that this
is called skills. So we'll say that this new column is called skills clean. Now
new column is called skills clean. Now we need to go through and fill out this
we need to go through and fill out this basically if statement. So if column
basically if statement. So if column name if skills equals in our case
name if skills equals in our case powerbi you have to give the correct
powerbi you have to give the correct proper uh punctuation for that that you
proper uh punctuation for that that you expect to see. We want it to be powerbi
expect to see. We want it to be powerbi with two capital letters for this. And
with two capital letters for this. And then from there we'll go ahead and just
then from there we'll go ahead and just click okay. This has a couple errors.
click okay. This has a couple errors. Specifically one none of the values
Specifically one none of the values transfer. So everything's null, but our
transfer. So everything's null, but our beloved PowerBI is transferred just
beloved PowerBI is transferred just fine. So let's go back into editing
fine. So let's go back into editing that. I can go to that step of add
that. I can go to that step of add conditional columns, click that settings
conditional columns, click that settings icon, and the first thing I want to do
icon, and the first thing I want to do is so we have this if and then we have
is so we have this if and then we have an else. And right now it's set to the
an else. And right now it's set to the value of null and that's why it's all
value of null and that's why it's all null. Instead, we want to select a
null. Instead, we want to select a column, specifically the column of
column, specifically the column of skills. Now, whenever we do this of
skills. Now, whenever we do this of okay, all these columns are filled in
okay, all these columns are filled in along with PowerBI. I'm also noticing
along with PowerBI. I'm also noticing that there's a PowerBI without a space
that there's a PowerBI without a space in it. I'm going to fix this one as
in it. I'm going to fix this one as well. So, we can go back into modifying
well. So, we can go back into modifying this column. We can add a clause in
this column. We can add a clause in here. We want to look in the skills
here. We want to look in the skills column equals PowerBI all lowercase. And
column equals PowerBI all lowercase. And I'm just going to copy this above and
I'm just going to copy this above and paste this in here. Click okay. And this
paste this in here. Click okay. And this one is now fixed. Okay. Next, remember
one is now fixed. Okay. Next, remember also we want to change SAS. So, I'm
also we want to change SAS. So, I'm going to go into here, add another
going to go into here, add another clause, skills equals SAS, and change
clause, skills equals SAS, and change this to all caps, and go ahead, click
this to all caps, and go ahead, click okay. Remember, the other one we want to
okay. Remember, the other one we want to do was SQL. But I'm going to actually
do was SQL. But I'm going to actually recommend a different approach besides
recommend a different approach besides conditional columns because look, we
conditional columns because look, we have things like SQL here. We have NoSQL
have things like SQL here. We have NoSQL here. We have TSQL down here. Once
here. We have TSQL down here. Once again, no SQL SQL server. Anyway,
again, no SQL SQL server. Anyway, there's a bunch of different SQLs in
there's a bunch of different SQLs in here. Conditional columns aren't going
here. Conditional columns aren't going to be able to fix that specifically
to be able to fix that specifically those cases without replacing the entire
those cases without replacing the entire contents. Instead, with that skills
contents. Instead, with that skills clean column, I want to replace values.
clean column, I want to replace values. And so, in cases where they have capital
And so, in cases where they have capital SQL, I want to have SQL in all caps. So,
SQL, I want to have SQL in all caps. So, replaced up here. And then let's also
replaced up here. And then let's also replace these other conditions of like
replace these other conditions of like no SQL. So once again, we can do replace
no SQL. So once again, we can do replace values SQL all lowercase. We'll do
values SQL all lowercase. We'll do capital SQL. Click okay. And bam. This
capital SQL. Click okay. And bam. This is looking a lot better. Now, there's a
is looking a lot better. Now, there's a bunch of other letters in here that you
bunch of other letters in here that you can feel free to go through and clean
can feel free to go through and clean up, but I'll leave that for you. This is
up, but I'll leave that for you. This is good enough for what I need. I do,
good enough for what I need. I do, however, want to clean up these columns.
however, want to clean up these columns. This is just unnecessary amount of
This is just unnecessary amount of different columns in here. So, I don't
different columns in here. So, I don't want two skills and skills clean. What
want two skills and skills clean. What I'll do is I'm going to remove the
I'll do is I'm going to remove the skills column. And then with skills
skills column. And then with skills clean, we're going to just rename that
clean, we're going to just rename that to skills. Also, not a fan of this
to skills. Also, not a fan of this order, so I'm going to drag it over.
order, so I'm going to drag it over. This is looking good. We'll go ahead and
This is looking good. We'll go ahead and close and apply. Now, looking at these
close and apply. Now, looking at these skills, let's go into focus mode for top
skills, let's go into focus mode for top skills. We can see that all these values
skills. We can see that all these values are now properly formatted. Not too bad.
are now properly formatted. Not too bad. So it shows the power of power query and
So it shows the power of power query and even doing simple thing like this like
even doing simple thing like this like text cleanup. And remember because all
text cleanup. And remember because all of these steps are in power query if we
of these steps are in power query if we ever have to refresh our data source
ever have to refresh our data source it's going to be still running through
it's going to be still running through the same data cleaning process. And so
the same data cleaning process. And so after actually going through that it
after actually going through that it still will apply it and you're going to
still will apply it and you're going to have your cleaned up values. All right
have your cleaned up values. All right it's now your turn to give it a try. We
it's now your turn to give it a try. We have some practice problems around
have some practice problems around practicing with splitting column by rows
practicing with splitting column by rows and also columns and then also how to
and also columns and then also how to create conditional columns. With that,
create conditional columns. With that, I'll see you in the next lesson. We're
I'll see you in the next lesson. We're going to be getting into how to append
going to be getting into how to append and also merge data sets. With that, see
and also merge data sets. With that, see you there.
Welcome to this second to last lesson in Power Query. We're going to get deeper
Power Query. We're going to get deeper and deeper into more advanced features.
and deeper into more advanced features. Specifically in this one, we're going to
Specifically in this one, we're going to be going over two major concepts.
be going over two major concepts. Specifically, how to append queries.
Specifically, how to append queries. Basically, put queries that have similar
Basically, put queries that have similar columns together on top of each other.
columns together on top of each other. And then merge queries, which is
And then merge queries, which is basically connecting two tables that
basically connecting two tables that have similar maybe column ids and then
have similar maybe column ids and then merging them together. We'll also have a
merging them together. We'll also have a bonus topic after the merge section
bonus topic after the merge section jumping into how to perform group by
jumping into how to perform group by analysis which is very similar to
analysis which is very similar to basically pivoting our data.
So jumping into our append example, we navigate into our project folder under
navigate into our project folder under data. We can see we have this data set
data. We can see we have this data set called job postings monthly. I'm going
called job postings monthly. I'm going go ahead and open it up. Now this is
go ahead and open it up. Now this is really common how my co-workers love to
really common how my co-workers love to send me data in that in this we have all
send me data in that in this we have all these different sheets within this
these different sheets within this workbook and each sheet is a different
workbook and each sheet is a different month. It's in very important to note
month. It's in very important to note that these sheets all have the same
that these sheets all have the same column format meaning they all go to
column format meaning they all go to column Q they maintain the same column
column Q they maintain the same column titles and I can verify this by going to
titles and I can verify this by going to another thing saying that it also goes
another thing saying that it also goes to Q. Anyway, we want to use append to
to Q. Anyway, we want to use append to make all 12 of these sheets here into
make all 12 of these sheets here into one single table. And we could do this
one single table. And we could do this with Power Query. For this example only,
with Power Query. For this example only, we're going to be starting with a blank
we're going to be starting with a blank workbook because after we get done with
workbook because after we get done with this, we're not going to keep it any
this, we're not going to keep it any further. The only point of this is to
further. The only point of this is to demonstrate how to do append. Anyway,
demonstrate how to do append. Anyway, start a blank report. Let's bring this
start a blank report. Let's bring this data into Power Query now by going to
data into Power Query now by going to get data. We're going to be getting this
get data. We're going to be getting this from Excel workbook. I guess I could
from Excel workbook. I guess I could also click it right there. Inside of our
also click it right there. Inside of our course project folder, I'm going to
course project folder, I'm going to navigate into data and select job
navigate into data and select job postings monthly and select open. Inside
postings monthly and select open. Inside of here, I have my Excel workbook and I
of here, I have my Excel workbook and I have all the different sheets. I need to
have all the different sheets. I need to now go through and I want all this data.
now go through and I want all this data. So, I'm going to select it all. From
So, I'm going to select it all. From there, we have the option to load it all
there, we have the option to load it all or get into Power Query. So, I'm going
or get into Power Query. So, I'm going to do that and select transform data.
to do that and select transform data. So, looking in our queries pane, we can
So, looking in our queries pane, we can see that all 12 of the sheets are loaded
see that all 12 of the sheets are loaded into here. And I can also verify by
into here. And I can also verify by scrolling on over. Looks like all the
scrolling on over. Looks like all the data is there. Looks good enough for me.
data is there. Looks good enough for me. Now we want to combine these queries
Now we want to combine these queries conveniently under the home tab. I can
conveniently under the home tab. I can come over here into combine. Select the
come over here into combine. Select the drop down. We have a few different
drop down. We have a few different options. We have merge. We're
options. We have merge. We're demonstrating append. I don't know if we
demonstrating append. I don't know if we can zoom in on this and see that append.
can zoom in on this and see that append. Basically we're appending on all the
Basically we're appending on all the different tables. With this clicking
different tables. With this clicking this dropown, we can append queries or
this dropown, we can append queries or append queries as new. Basically a new
append queries as new. Basically a new query. If I do append queries with that
query. If I do append queries with that December 2024 selected, it's going to do
December 2024 selected, it's going to do the modifications inside that current
the modifications inside that current query. So in this case, if I were to
query. So in this case, if I were to just append on January in this case,
just append on January in this case, it's going to append it on to that
it's going to append it on to that query. And that's not necessarily what I
query. And that's not necessarily what I want. Instead, what I'm going to do is
want. Instead, what I'm going to do is come up here to a a combine, select
come up here to a a combine, select append queries, append queries as new to
append queries, append queries as new to a new query. You can do two tables or
a new query. You can do two tables or three or more tables in our case. And
three or more tables in our case. And then we need to move all the ones we
then we need to move all the ones we want over to the other side. In my case,
want over to the other side. In my case, I accidentally added December twice. So
I accidentally added December twice. So make sure you don't do that as all you
make sure you don't do that as all you got to do is just select remove. And now
got to do is just select remove. And now all the ones were selected. Go and
all the ones were selected. Go and select okay. Now here we have our append
select okay. Now here we have our append query. If I look at the source step by
query. If I look at the source step by just open this up, we can see that all
just open this up, we can see that all we're doing is combining all these
we're doing is combining all these different other queries. We're going to
different other queries. We're going to name this as data jobs append. Now,
name this as data jobs append. Now, before we get into closing and loading
before we get into closing and loading this, we don't want to close and load
this, we don't want to close and load all these other queries in here. Also, I
all these other queries in here. Also, I don't really like the organization of
don't really like the organization of this. What I'm going to do is I'm going
this. What I'm going to do is I'm going to select all of these and hold control
to select all of these and hold control to select all the different monthly
to select all the different monthly queries. And then I'm going to
queries. And then I'm going to rightclick it and select move to group.
rightclick it and select move to group. We're going to create a new group for
We're going to create a new group for this and call this data jobs monthly.
this and call this data jobs monthly. Real original. Okay. So now it makes it
Real original. Okay. So now it makes it a lot easier to hide these queries. And
a lot easier to hide these queries. And then the other query, if you will, the
then the other query, if you will, the data jobs append is inside other
data jobs append is inside other queries. All right, one last thing,
queries. All right, one last thing, right? That the one that I actually
right? That the one that I actually really care about is I don't want to
really care about is I don't want to load this. So I'm going to rightclick
load this. So I'm going to rightclick one of the queries and I'm going to
one of the queries and I'm going to uncheck enable load and it's going to go
uncheck enable load and it's going to go to italics. So know that to sign
to italics. So know that to sign symbolize that that's what happened.
symbolize that that's what happened. Then once we did it all for these, I'm
Then once we did it all for these, I'm going to hit close and apply. So we can
going to hit close and apply. So we can load it in and only that one query is
load it in and only that one query is loaded in. You will notice it will
loaded in. You will notice it will evaluate the other ones because it needs
evaluate the other ones because it needs to evaluate them and go through them,
to evaluate them and go through them, but only one will load. Inside the data
but only one will load. Inside the data pane, we can see that one is loaded in.
pane, we can see that one is loaded in. As always, we should go into table view
As always, we should go into table view and verify that yep, everything's
and verify that yep, everything's looking like it's right. I can also see
looking like it's right. I can also see there that we have 479,000
there that we have 479,000 rows, which is the number we would
rows, which is the number we would expect to see for all our different data
expect to see for all our different data jobs posting. Just so it doesn't go
jobs posting. Just so it doesn't go without saying this data is exactly the
without saying this data is exactly the same that we've operated previously
same that we've operated previously with. I just broke it up into different
with. I just broke it up into different sheets. Anyway, with this just verifying
sheets. Anyway, with this just verifying it, I can throw in something like a line
it, I can throw in something like a line chart. Minimize this filters. Then put
chart. Minimize this filters. Then put job posted date on the x-axis and then a
job posted date on the x-axis and then a count of jobs in the y-axis. Remember,
count of jobs in the y-axis. Remember, we got to drill down. We can see this on
we got to drill down. We can see this on a quarterly basis, monthly basis, and
a quarterly basis, monthly basis, and then daily basis. and inspecting. It
then daily basis. and inspecting. It doesn't look like there's any gaps
doesn't look like there's any gaps between January all the way to December.
Now that we have a pen down, let's move into merge, which is slightly more
into merge, which is slightly more complex. Okay, so this is usually the
complex. Okay, so this is usually the use case that I find for it. Remember,
use case that I find for it. Remember, we have our data in this format.
we have our data in this format. Specifically, we have our fact table
Specifically, we have our fact table here and then our other dimensional
here and then our other dimensional tables. Let's say now we need to give
tables. Let's say now we need to give this data to our boss, but they haven't
this data to our boss, but they haven't watched this tutorial. So, they don't
watched this tutorial. So, they don't know the difference between fact and
know the difference between fact and dimensional tables or how to establish
dimensional tables or how to establish relationships. They just want a flat
relationships. They just want a flat table with everything on it. And this is
table with everything on it. And this is the table that we're going to create
the table that we're going to create with this specifically. You can see from
with this specifically. You can see from it, it looks very similar to our job
it, it looks very similar to our job postings fact table. But if I scroll all
postings fact table. But if I scroll all the way to the right, it also has all
the way to the right, it also has all those skills and then also that skill
those skills and then also that skill type in it. What we're going to do is
type in it. What we're going to do is merge the data set. Now, it's important
merge the data set. Now, it's important to remember this. So, look at this
to remember this. So, look at this table, right? The job skills flat. It is
table, right? The job skills flat. It is now 2.3 million rows. If we go back to
now 2.3 million rows. If we go back to job posting fact, it's 478,000.
job posting fact, it's 478,000. Why is that? Well, whenever we merge it,
Why is that? Well, whenever we merge it, so going back to that flat table, we can
so going back to that flat table, we can see like in this case, these job IDs are
see like in this case, these job IDs are repeating. So, this is a repeating job
repeating. So, this is a repeating job posting in order to capture all the
posting in order to capture all the different skills on different rows. So,
different skills on different rows. So, something to think about whenever we get
something to think about whenever we get to the end of this. Anyway, let's jump
to the end of this. Anyway, let's jump into doing this. So for the file for
into doing this. So for the file for this and the remaining portion of this
this and the remaining portion of this lesson, you can use what we had from the
lesson, you can use what we had from the previous lesson on advanced
previous lesson on advanced transformations or you can just open up
transformations or you can just open up this file in the project folder on
this file in the project folder on advanced transformations and use that.
advanced transformations and use that. Our final results are going to be in
Our final results are going to be in that 3.5_merge.
that 3.5_merge. So let's jump into it. Remember we want
So let's jump into it. Remember we want to combine our job postings fact table
to combine our job postings fact table with our skills. Because of this, we
with our skills. Because of this, we have to merge in this connector uh table
have to merge in this connector uh table first and then in our finally skills dim
first and then in our finally skills dim table. So, it's going to be more of a
table. So, it's going to be more of a multi-step process. In order to do this,
multi-step process. In order to do this, you know what we got to do? Go into
you know what we got to do? Go into power query editor. So, let's jump into
power query editor. So, let's jump into our first step. We're going to want to
our first step. We're going to want to connect our job postings fact to skills
connect our job postings fact to skills job dim. So, we have the job postings
job dim. So, we have the job postings fact connected. I can come up here in
fact connected. I can come up here in the home tab to combine. And we have
the home tab to combine. And we have once again similar options of merge
once again similar options of merge queries and merge queries as new. I
queries and merge queries as new. I don't want to affect our original job
don't want to affect our original job postings fact table. So I'm going to say
postings fact table. So I'm going to say merge queries as new. And it's going to
merge queries as new. And it's going to say, hey, select the tables and matching
say, hey, select the tables and matching columns to create a merge table. We do
columns to create a merge table. We do want the job postings fact table. And
want the job postings fact table. And then we want the skills job dim. What
then we want the skills job dim. What are we going to be connecting them on?
are we going to be connecting them on? Well, the job ID. So we need to make
Well, the job ID. So we need to make sure we select both of those. Now, what
sure we select both of those. Now, what do we select next for the join kind?
do we select next for the join kind? There are underneath here six different
There are underneath here six different ones that we have. So, we're going to
ones that we have. So, we're going to walk through each of these six different
walk through each of these six different types of joins. And in order to do this,
types of joins. And in order to do this, it's important to understand we're going
it's important to understand we're going to be showing some visuals with it. And
to be showing some visuals with it. And in this, we're going to be demonstrating
in this, we're going to be demonstrating how whenever you join table A to table
how whenever you join table A to table B, what data is included and the visuals
B, what data is included and the visuals associated with this. And this
associated with this. And this represents with the shaded color in blue
represents with the shaded color in blue represents what data we're going to keep
represents what data we're going to keep with this. Just to be clear, table A in
with this. Just to be clear, table A in our case is the job postings fact table
our case is the job postings fact table and then table B is the skills job dim.
and then table B is the skills job dim. So the first option is left outer and
So the first option is left outer and with that we're going to select all from
with that we're going to select all from the first and then matching from the
the first and then matching from the second. So with that, this demonstrates
second. So with that, this demonstrates that no matter what, everything from
that no matter what, everything from that table A, the job postings fact
that table A, the job postings fact table is going to be included. And then
table is going to be included. And then in table B, only things that match up
in table B, only things that match up will be included. So that's why only
will be included. So that's why only that center portion is colored. Now with
that center portion is colored. Now with this, we can see down at the bottom, the
this, we can see down at the bottom, the selection matches 410,000 out of 478,000
selection matches 410,000 out of 478,000 rows from the first table. Basically
rows from the first table. Basically what this saying is 410,000 job postings
what this saying is 410,000 job postings have associated skill or skills with it.
have associated skill or skills with it. This is actually a perfectly fine join
This is actually a perfectly fine join to use, but we need to talk about the
to use, but we need to talk about the other five still. Next up is a right
other five still. Next up is a right outer and this does all from the second
outer and this does all from the second and then matching from the first. This
and then matching from the first. This is basically just opposite from the last
is basically just opposite from the last one. Table B or our skills job dim.
one. Table B or our skills job dim. We're going to keep every single value
We're going to keep every single value from that and then only matching records
from that and then only matching records from our leftmost table or that job
from our leftmost table or that job postings fact table. Inspecting this
postings fact table. Inspecting this down at the bottom, we can see that 2.2
down at the bottom, we can see that 2.2 million out of 2.2 million rows from the
million out of 2.2 million rows from the second table are matched. But that's not
second table are matched. But that's not the full story. Remember whenever we did
the full story. Remember whenever we did left outer, it basically said that of
left outer, it basically said that of the 478,000
the 478,000 job postings, there were only 410,000
job postings, there were only 410,000 that obtained that had skills. So what's
that obtained that had skills. So what's happening now with this write outer is
happening now with this write outer is that there's about 68,000
that there's about 68,000 differences or job postings without a
differences or job postings without a skill. Therefore, whenever we do this
skill. Therefore, whenever we do this route out right outer, we would be
route out right outer, we would be missing those 68,000 jobs because they
missing those 68,000 jobs because they don't have a skill in our final join.
don't have a skill in our final join. Because of that, we're not going to use
Because of that, we're not going to use a right outer because we want all the
a right outer because we want all the job postings. Next up, we're going to
job postings. Next up, we're going to skip over full outer and get into inner.
skip over full outer and get into inner. In this, it only matches matching rows.
In this, it only matches matching rows. Looking at this visually, we can see
Looking at this visually, we can see that okay, only the matching rows from
that okay, only the matching rows from table A and table B are going to be
table A and table B are going to be included in that. So if we remember from
included in that. So if we remember from our write outer, what do you think is
our write outer, what do you think is going to happen? Well, it tells us only
going to happen? Well, it tells us only 410,000 of the 478,000 job postings are
410,000 of the 478,000 job postings are going to be included in this. If we
going to be included in this. If we scroll over, we also see that from the
scroll over, we also see that from the second table, all the skills would be
second table, all the skills would be included. So that makes sense with that
included. So that makes sense with that because every single skill has an
because every single skill has an associated job posting. Anyway, we're
associated job posting. Anyway, we're not going to use enter for this. All
not going to use enter for this. All right, next up is left anti. And in
right, next up is left anti. And in this, it is rows only in the first
this, it is rows only in the first table. In this case, we're only going to
table. In this case, we're only going to be keeping those in table A, so the job
be keeping those in table A, so the job posting facts table that have no
posting facts table that have no correlated skill with it. And we confirm
correlated skill with it. And we confirm this by saying, hey, this selection
this by saying, hey, this selection excludes 410,000 of 478,000. So
excludes 410,000 of 478,000. So basically this is going to return 68,000
basically this is going to return 68,000 job postings without any skills. This is
job postings without any skills. This is completely useless at least in our case.
completely useless at least in our case. Moving on to right anti. This one is
Moving on to right anti. This one is going to have only rows only in the
going to have only rows only in the second. This is only going to include
second. This is only going to include rows from the right table that do not
rows from the right table that do not have any matches in the left table,
have any matches in the left table, which means that there's no rows. And as
which means that there's no rows. And as we can see, the selection excludes all
we can see, the selection excludes all 227,000 of the 227,000. Sorry, 2.2
227,000 of the 227,000. Sorry, 2.2 million. So no matches are going to be
million. So no matches are going to be done with this one. Also completely
done with this one. Also completely useless in our case. All right, last one
useless in our case. All right, last one is full outer and that's going to be
is full outer and that's going to be doing all rows from both. This one will
doing all rows from both. This one will recruit all results from table A and
recruit all results from table A and table B whether they match or not. In
table B whether they match or not. In our case, we do know that table B
our case, we do know that table B matches all of table A. So whenever we
matches all of table A. So whenever we do this, there's not going to be any
do this, there's not going to be any problems. And actually this full outer
problems. And actually this full outer in our case is basically the same thing
in our case is basically the same thing as a left outer because like I said all
as a left outer because like I said all the skills are associated with a certain
the skills are associated with a certain job posting and it gives us that similar
job posting and it gives us that similar response of the selection matches
response of the selection matches 410,000 out of 478,000
410,000 out of 478,000 that basically have skills and
that basically have skills and everything from the second table matches
everything from the second table matches completely. We're going to go with this
completely. We're going to go with this full outer. I'm going to click okay. So
full outer. I'm going to click okay. So we have this merge data in. I'm going to
we have this merge data in. I'm going to go ahead and change this name from merge
go ahead and change this name from merge one to job skills flat. Also, you're
one to job skills flat. Also, you're going to notice with this, especially
going to notice with this, especially with this large of a data set, that when
with this large of a data set, that when we start doing this, it takes a while to
we start doing this, it takes a while to load. So, one of the drawbacks of doing
load. So, one of the drawbacks of doing merge in Power Query, if your computer's
merge in Power Query, if your computer's not robust enough to handle this, feel
not robust enough to handle this, feel free to just watch along so you can gain
free to just watch along so you can gain the experience at least seeing what
the experience at least seeing what happens. No need to get frustrated
happens. No need to get frustrated because you don't have enough RAM in
because you don't have enough RAM in your computer to handle this. So now
your computer to handle this. So now scrolling all over to the right, what we
scrolling all over to the right, what we can see is that we did merge on that
can see is that we did merge on that skills job dim table into our job
skills job dim table into our job posting flat table, which is all the
posting flat table, which is all the columns to the left. But they merged it
columns to the left. But they merged it in with this in a table. I'm actually
in with this in a table. I'm actually going to click on this just to show what
going to click on this just to show what it is. And it's going to navigate into
it is. And it's going to navigate into this specific row of the table. And so
this specific row of the table. And so what we can see from this is that we
what we can see from this is that we clicked into one row. That row was for
clicked into one row. That row was for the job ID of five. and it had all of
the job ID of five. and it had all of these different skills associated with
these different skills associated with it. So, pretty cool. We can navigate
it. So, pretty cool. We can navigate into it. Overall, not too important. We
into it. Overall, not too important. We need to actually do this step. We need
need to actually do this step. We need to actually do this for all the rows.
to actually do this for all the rows. And we can do this by scrolling on over
And we can do this by scrolling on over here. And up here at the top, there's
here. And up here at the top, there's this expand icon. Whenever I click it, I
this expand icon. Whenever I click it, I can either expand or I can also
can either expand or I can also aggregate it based on the sum of these
aggregate it based on the sum of these things in here, which is not what we
things in here, which is not what we want to do. We want to actually expand
want to do. We want to actually expand it out. And with this, it's going to
it out. And with this, it's going to give us the job ID and the skill ID.
give us the job ID and the skill ID. Remember, in job posting facts, we
Remember, in job posting facts, we already have the job ID. So, I don't
already have the job ID. So, I don't want to repeat it again here. So, I'm
want to repeat it again here. So, I'm only going to import in the skill ID and
only going to import in the skill ID and click okay. It's now expanded out. And
click okay. It's now expanded out. And if I scroll on over, I can see now that
if I scroll on over, I can see now that these job postings are duplicated
these job postings are duplicated because this case, job ID is repeated
because this case, job ID is repeated multiple times for five, nine, and
multiple times for five, nine, and whatnot. But we're not done. Remember,
whatnot. But we're not done. Remember, we just connected the job postings fact
we just connected the job postings fact table to SC skills job dim. We still
table to SC skills job dim. We still need to connect to the skills dim table.
need to connect to the skills dim table. Because of that, we need to do another
Because of that, we need to do another merge. With job skills flat table
merge. With job skills flat table selected, I'm going to go into the home
selected, I'm going to go into the home tab. I'm going to combine and we need to
tab. I'm going to combine and we need to merge. Again, I don't need to create a
merge. Again, I don't need to create a new query. We can continue working in
new query. We can continue working in this one. So, we're just going to do
this one. So, we're just going to do merge queries. Now for this one from the
merge queries. Now for this one from the job skills flat table we want to connect
job skills flat table we want to connect on that skill ID on skills job dim and
on that skill ID on skills job dim and we want to connect to the skills dim
we want to connect to the skills dim table on that skill ID. So for this join
table on that skill ID. So for this join which one do you think we're going to
which one do you think we're going to use for this in the fact that we want to
use for this in the fact that we want to keep everything from the job postings
keep everything from the job postings fact table while also putting all of our
fact table while also putting all of our skill information into this table. Well,
skill information into this table. Well, with left outer, what we're seeing is
with left outer, what we're seeing is that we're going to match 2.2 million
that we're going to match 2.2 million out of 2.3 million rows from the first
out of 2.3 million rows from the first table. And why is there a difference in
table. And why is there a difference in this? Well, it has to do with the fact
this? Well, it has to do with the fact that there are some jobs that don't have
that there are some jobs that don't have a skill. In our case, this left outer is
a skill. In our case, this left outer is going to work. And also, we can see we
going to work. And also, we can see we get the same output for full outer. In
get the same output for full outer. In this case, once again, both of those are
this case, once again, both of those are perfectly fine to use. I'm going to go
perfectly fine to use. I'm going to go ahead and click okay because I know it's
ahead and click okay because I know it's going to preserve all the job postings
going to preserve all the job postings in the first table and just match up
in the first table and just match up those skills for all those that should
those skills for all those that should have a match. Now that we have this
have a match. Now that we have this skills dim added once again it's going
skills dim added once again it's going to provide it in a table like format. I
to provide it in a table like format. I can click into it so we can investigate
can click into it so we can investigate it. You don't need to do this portion
it. You don't need to do this portion but what I would expect to see is since
but what I would expect to see is since this is only zero we should only see the
this is only zero we should only see the skill for zero. And ding ding ding
skill for zero. And ding ding ding that's what we got. Zero SQL and it's
that's what we got. Zero SQL and it's the type programming. All right, I'm
the type programming. All right, I'm gonna get rid of this. I was just doing
gonna get rid of this. I was just doing that for demo. So, what we need to do is
that for demo. So, what we need to do is come up here to that skills dim table
come up here to that skills dim table and actually expand it. Once again, we
and actually expand it. Once again, we have a skill ID already in there. We
have a skill ID already in there. We don't want that. We're going to uncheck
don't want that. We're going to uncheck that and then expand out the other two
that and then expand out the other two remaining columns. All right, not too
remaining columns. All right, not too bad. We have this in here. I just want
bad. We have this in here. I just want to do a little bit of cleanup.
to do a little bit of cleanup. Specifically, I don't need this skill ID
Specifically, I don't need this skill ID column. So, I'm going to end up removing
column. So, I'm going to end up removing that column. And then we're going to
that column. And then we're going to rename both this and instead of being
rename both this and instead of being skills dim skills, it's just going to be
skills dim skills, it's just going to be skills. And I'll change this one to
skills. And I'll change this one to skill type. Now we're complete and we've
skill type. Now we're complete and we've cleaned up this table, this job skills
cleaned up this table, this job skills flat. We're going to now load this into
flat. We're going to now load this into PowerBI and just visualize it to make
PowerBI and just visualize it to make sure that it's working correctly. But I
sure that it's working correctly. But I do want to show something specifically.
do want to show something specifically. We just created a new table. And this
We just created a new table. And this table has like 2.2 million rows in it.
table has like 2.2 million rows in it. It's a lot bigger. Anyway, our current
It's a lot bigger. Anyway, our current file for 3.4 for advanced
file for 3.4 for advanced transformations that I'm working right
transformations that I'm working right now is 39 megabytes or 39,000 kilobytes.
now is 39 megabytes or 39,000 kilobytes. Let's see how big it gets after we save
Let's see how big it gets after we save the file. So, first I'm going to close
the file. So, first I'm going to close and load it. And now it's loaded in. As
and load it. And now it's loaded in. As we can see here, I'm going to go ahead
we can see here, I'm going to go ahead and now save this file. Navigating back
and now save this file. Navigating back to here. This bad boy went from 39
to here. This bad boy went from 39 megabytes to 76 megabytes or 76,000
megabytes to 76 megabytes or 76,000 kilobytes. It basically doubled in size.
kilobytes. It basically doubled in size. So something to think about whenever
So something to think about whenever you're building these type of files. It
you're building these type of files. It is going to make your file size a lot
is going to make your file size a lot bigger, make it even harder to share.
bigger, make it even harder to share. Anyway, one thing that's going on here
Anyway, one thing that's going on here which is really weird and I don't want
which is really weird and I don't want it to do is this job postings flat table
it to do is this job postings flat table has relationships with the job ID of the
has relationships with the job ID of the job posting fact and then it has this
job posting fact and then it has this secondary one with the company ID of
secondary one with the company ID of this company dim. This dotted line means
this company dim. This dotted line means that it's not the primary relationship.
that it's not the primary relationship. Anyway, I don't want any of these. I'm
Anyway, I don't want any of these. I'm going to delete both these relationships
going to delete both these relationships in here because we don't want that. I'm
in here because we don't want that. I'm going to create a new page called merge.
going to create a new page called merge. And we're just going to demo real quick.
And we're just going to demo real quick. Make sure we have the correct data in
Make sure we have the correct data in here. Specifically, what are the top
here. Specifically, what are the top skills and data? I'm going to uh copy
skills and data? I'm going to uh copy that. And I'm going to paste that in
that. And I'm going to paste that in here. And I put some text boxes in here
here. And I put some text boxes in here just to keep track. Right. This side
just to keep track. Right. This side over here, we're going to be analyzing
over here, we're going to be analyzing the star schema data that we use from
the star schema data that we use from the job postings fact table and the
the job postings fact table and the skills down. We now want to see what our
skills down. We now want to see what our data looks like in job skills flat. So
data looks like in job skills flat. So I'll remove both the Y and the X- axis.
I'll remove both the Y and the X- axis. Navigate into job skills flat. For the
Navigate into job skills flat. For the Y-axis, we'll drive drop in skills. And
Y-axis, we'll drive drop in skills. And for the X-axis, we're going to do a
for the X-axis, we're going to do a count. We want to do a count of the job
count. We want to do a count of the job IDs. So I need to change this over to
IDs. So I need to change this over to count. Okay. The purpose of this was to
count. Okay. The purpose of this was to well verify. Is it the same? So skills
well verify. Is it the same? So skills are at 244,416
are at 244,416 for Python and 244,416.
for Python and 244,416. So this flat table is good. The only
So this flat table is good. The only thing we have to remember, right, is
thing we have to remember, right, is navigating to this table view with job
navigating to this table view with job skills flat selected. There are, as you
skills flat selected. There are, as you can see, multiple different job IDs
can see, multiple different job IDs because some jobs have multiple
because some jobs have multiple different skills. So whoever we give
different skills. So whoever we give this data set to, they have to be sure
this data set to, they have to be sure that they know how they're analyzing it.
that they know how they're analyzing it. Now, what is if we need to send this to
Now, what is if we need to send this to our boss? Well, the easiest way is
our boss? Well, the easiest way is inside of this table view underneath
inside of this table view underneath data. We can write uh we can select
data. We can write uh we can select those three dots. And from there, you're
those three dots. And from there, you're going to select copy table. And in my
going to select copy table. And in my case, it took a couple minutes to copy
case, it took a couple minutes to copy it into the clipboard. Now, I'm going to
it into the clipboard. Now, I'm going to go ahead and just paste it right here
go ahead and just paste it right here into a blank Excel spreadsheet. And
into a blank Excel spreadsheet. And silly me, it says the data set's too
silly me, it says the data set's too large, right? Cuz we had 2.2 million
large, right? Cuz we had 2.2 million rows of data. There's only one million
rows of data. There's only one million about 1 million rows in Excel. So, not
about 1 million rows in Excel. So, not all of it's going to go into here, but
all of it's going to go into here, but you get the idea. Scroll on down. Almost
you get the idea. Scroll on down. Almost a million rows of data inside of here.
All right, so moving into our second and really bonus round of using group eye.
really bonus round of using group eye. Let's say we get back from our boss that
Let's say we get back from our boss that hey, he didn't like that you had to send
hey, he didn't like that you had to send him multiple different Excel files to
him multiple different Excel files to get those 2.2 million job postings with
get those 2.2 million job postings with all those skills. instead he just wants
all those skills. instead he just wants you to aggregate it all together and
you to aggregate it all together and then give him those results. That way
then give him those results. That way the table's much smaller. Well, we can
the table's much smaller. Well, we can use group by for this. So, let's
use group by for this. So, let's navigate back into the power query
navigate back into the power query editor. And we don't necessarily need to
editor. And we don't necessarily need to load this job skills flat table anymore
load this job skills flat table anymore because like I said, my boss doesn't
because like I said, my boss doesn't really want it. So, we're going to
really want it. So, we're going to uncheck enable load. It'll say, hey,
uncheck enable load. It'll say, hey, there's potential possible data loss
there's potential possible data loss warning. Not worried about that. It
warning. Not worried about that. It ain't going to happen. But seriously,
ain't going to happen. But seriously, it's not. And we want to end up using
it's not. And we want to end up using this table to get an aggregation of
this table to get an aggregation of things. We're going to end using under
things. We're going to end using under the transform tab group by. I could
the transform tab group by. I could start by doing a group by here, but this
start by doing a group by here, but this is going to do it within the current
is going to do it within the current query. I don't want to do that. So what
query. I don't want to do that. So what we're going to do is we're going to
we're going to do is we're going to create a new not duplicate, but
create a new not duplicate, but reference query. Now, with this new
reference query. Now, with this new query that I've renamed to job skills
query that I've renamed to job skills group by, we're going to perform group
group by, we're going to perform group by. And we're going to keep it simple at
by. And we're going to keep it simple at first. I'm going to just we want to look
first. I'm going to just we want to look at specifically that skills column. And
at specifically that skills column. And with this, we just want a skill count.
with this, we just want a skill count. And so, this is going to count the rows.
And so, this is going to count the rows. And we don't select the column because
And we don't select the column because we're just counting the rows. We'll go
we're just counting the rows. We'll go ahead and click okay. And we can
ahead and click okay. And we can basically see that the data was now
basically see that the data was now group by or if you will pivoted in that
group by or if you will pivoted in that we're getting skill counts for all the
we're getting skill counts for all the different skills that we have. Now we're
different skills that we have. Now we're not limited just doing one column. I can
not limited just doing one column. I can go back into this group rows and I
go back into this group rows and I actually know that he wants more
actually know that he wants more information more than just the skills
information more than just the skills specifically. He's curious of breaking
specifically. He's curious of breaking down the count of skills based on not
down the count of skills based on not only the skills but also on something
only the skills but also on something like the job title short column. And we
like the job title short column. And we can still do a skill count for this. I'm
can still do a skill count for this. I'm going go ahead and click okay. And now
going go ahead and click okay. And now it's breaking down by skills and that
it's breaking down by skills and that job title short column. So this is going
job title short column. So this is going to be the final table we're export. But
to be the final table we're export. But I want to show and demonstrate one thing
I want to show and demonstrate one thing specifically. If we were to go back into
specifically. If we were to go back into that group rows, we have to be very
that group rows, we have to be very careful about how we're grouping and
careful about how we're grouping and what we're aggregating by. Specifically,
what we're aggregating by. Specifically, let's say we were trying to do the
let's say we were trying to do the median value of something like the
median value of something like the yearly salary. And we'll say this is a
yearly salary. And we'll say this is a median salary. So this can be done and
median salary. So this can be done and this is like I said showing that median
this is like I said showing that median salary. But what my boss is going to
salary. But what my boss is going to take and do is he's going to end up
take and do is he's going to end up trying to most likely find out what is
trying to most likely find out what is overall SQL. What is the median salary
overall SQL. What is the median salary overall? And then you'd be taking a
overall? And then you'd be taking a median of this median salary column. So
median of this median salary column. So whenever you start getting to other
whenever you start getting to other aggregations with group eyes, I don't
aggregations with group eyes, I don't recommend it because you're not going to
recommend it because you're not going to get the actual results unless you look
get the actual results unless you look at the median for the entire data set.
at the median for the entire data set. And this can be applied similarly if you
And this can be applied similarly if you were doing like an average salary and
were doing like an average salary and then try to take an average of an
then try to take an average of an average. It's not going to work out to
average. It's not going to work out to what you want. Long story short, if
what you want. Long story short, if you're doing any type of aggregation or
you're doing any type of aggregation or group by, I would leave it to things
group by, I would leave it to things like count and also count distinct rows.
like count and also count distinct rows. Besides that, that's about it. So now we
Besides that, that's about it. So now we have the final table that we want. I
have the final table that we want. I have it loading in. We disenbled the
have it loading in. We disenbled the load a job skills flat. I'm going to go
load a job skills flat. I'm going to go in and close and apply this. We can see
in and close and apply this. We can see now that that job skills flat table's
now that that job skills flat table's gone and we only have that job skills
gone and we only have that job skills group by. And let's just see real quick.
group by. And let's just see real quick. Remember we haven't saved just yet. So
Remember we haven't saved just yet. So this file size is 76 megabytes as we're
this file size is 76 megabytes as we're shown right here. Whenever I actually
shown right here. Whenever I actually save this now with only the group by and
save this now with only the group by and removing that big old flat table, we get
removing that big old flat table, we get back down to basically 39 megabytes,
back down to basically 39 megabytes, which much smaller. Group eyes is a lot
which much smaller. Group eyes is a lot better. So once again, let's make sure
better. So once again, let's make sure that we're getting the correct results
that we're getting the correct results for our group by. And for this, we're
for our group by. And for this, we're going to be once again comparing it to
going to be once again comparing it to that star schema data. So I can go into
that star schema data. So I can go into that skill stat, copy this bad boy, and
that skill stat, copy this bad boy, and then paste it right into here. I'm going
then paste it right into here. I'm going to copy and also drag it over here.
to copy and also drag it over here. Remove the values inside of it. Add in
Remove the values inside of it. Add in skills to the y-axis and skill count to
skills to the y-axis and skill count to the x-axis and are we going to get the
the x-axis and are we going to get the same results? Python 244,416
same results? Python 244,416 Python 2444,46416.
Python 2444,46416. Now, what's also neat about this is
Now, what's also neat about this is because we kept that job title short in
because we kept that job title short in there. I can then even drag job title
there. I can then even drag job title short into the small multitudes and it's
short into the small multitudes and it's showing a 4x4 grid or a 2 x two grid.
showing a 4x4 grid or a 2 x two grid. I'm not really liking this. Under small
I'm not really liking this. Under small multitudes under format visual, I can go
multitudes under format visual, I can go to the number of columns and change it
to the number of columns and change it to one. And then for this visual, I just
to one. And then for this visual, I just want to have a filter on the skills
want to have a filter on the skills itself to only just show the top five
itself to only just show the top five filter or top five skills. We'll say top
filter or top five skills. We'll say top five. And I'll drag skill count into
five. And I'll drag skill count into there to do sum of skill count. All
there to do sum of skill count. All right. Now, boom. Top five skills are
right. Now, boom. Top five skills are AWS, Azure, Python, SQL, and Tableau.
AWS, Azure, Python, SQL, and Tableau. And we can actually scroll through and
And we can actually scroll through and see it for all the other different job
see it for all the other different job titles as well. One quick note, because
titles as well. One quick note, because we deleted that job skills flat table,
we deleted that job skills flat table, this visualization that we built
this visualization that we built previously is not going to work for the
previously is not going to work for the flat table. So, we're going to have to
flat table. So, we're going to have to go ahead and just delete this page. All
go ahead and just delete this page. All right, you now have some practice
right, you now have some practice problems to go through and get more
problems to go through and get more familiar with using appends, merges, and
familiar with using appends, merges, and also group buys. After that, we'll be
also group buys. After that, we'll be jumping into our last lesson to do a
jumping into our last lesson to do a deeper dive on the M language, which is
deeper dive on the M language, which is what is powering Power Query. With that,
what is powering Power Query. With that, I'll see you in the next one.
All right, this is the last lesson on Power Query and we're jumping into a
Power Query and we're jumping into a topic on the M language. Little sad that
topic on the M language. Little sad that is the last one on Power Query cuz Power
is the last one on Power Query cuz Power Quer is one of my favorite topics.
Quer is one of my favorite topics. Anyway, for this M language, don't be
Anyway, for this M language, don't be int uh intimidated because we're not
int uh intimidated because we're not going to be uh like programming experts
going to be uh like programming experts by the end of this. Instead, I just want
by the end of this. Instead, I just want you to have a basic understanding of
you to have a basic understanding of what is the purpose of this language
what is the purpose of this language that powers Power Query. And also, by
that powers Power Query. And also, by the end of this, I'm going to give you
the end of this, I'm going to give you some techniques with AI bots like
some techniques with AI bots like ChachiBT in order to help you out if you
ChachiBT in order to help you out if you ever find yourself nearing needing to
ever find yourself nearing needing to modify an M language query.
So what the heck is M language? Well, M language is Power Query's query language
language is Power Query's query language for basically data manipulation and
for basically data manipulation and transformation. It's what's under the
transformation. It's what's under the hood in the Power Query editor that's
hood in the Power Query editor that's actually doing all of our different ETL
actually doing all of our different ETL process or extract, transform, load.
process or extract, transform, load. Now, it's important to understand we can
Now, it's important to understand we can interact with the guey of the Power
interact with the guey of the Power Query editor and it just generates the M
Query editor and it just generates the M language itself. We don't necessarily
language itself. We don't necessarily need to actually do the M language or do
need to actually do the M language or do the M language. We don't need
the M language. We don't need necessarily type out the M language. And
necessarily type out the M language. And as we demonstrated, right? So in the
as we demonstrated, right? So in the case of our job postings fact table that
case of our job postings fact table that we've been manipulating through this,
we've been manipulating through this, right? We've gone through and applied in
right? We've gone through and applied in this case 1 2 3 4 five different steps.
this case 1 2 3 4 five different steps. And we can see each of these steps. One,
And we can see each of these steps. One, we can see it inside of the formula bar
we can see it inside of the formula bar itself. So in this case, this change
itself. So in this case, this change type step, it includes this entire step
type step, it includes this entire step right here. Or we can even see all of
right here. Or we can even see all of the steps inside the advanced editor.
the steps inside the advanced editor. And looking at this change type, this
And looking at this change type, this entire thing, this whole formula right
entire thing, this whole formula right here is the same thing that was in the
here is the same thing that was in the formula bar on this single row. And we
formula bar on this single row. And we can see 1 2 3 4 five different rows in
can see 1 2 3 4 five different rows in here for the five different steps. At
here for the five different steps. At the end of this video, we're going to be
the end of this video, we're going to be demonstrating how to actually move like
demonstrating how to actually move like query like this into another query. Say
query like this into another query. Say we have a new PowerBI file we're
we have a new PowerBI file we're starting with and we just want this
starting with and we just want this table alone. We're going to show you how
table alone. We're going to show you how to actually do this cuz I find it pretty
to actually do this cuz I find it pretty common, but we'll save that for later.
All right, for this lesson, we're going to be working in the same file as last
to be working in the same file as last time. Specifically, we're going to be
time. Specifically, we're going to be starting off from that 3.5 merge. You
starting off from that 3.5 merge. You can also just continue to work in that
can also just continue to work in that same PowerBI file. Doesn't really
same PowerBI file. Doesn't really matter. Anyway, here I have it loaded. I
matter. Anyway, here I have it loaded. I do want to clean it up because remember
do want to clean it up because remember in the last lesson we created this flat
in the last lesson we created this flat table and then also this group eye. We
table and then also this group eye. We don't need any of that and we don't need
don't need any of that and we don't need any of these pages associated with it.
any of these pages associated with it. First, I'm going get rid of those pages.
First, I'm going get rid of those pages. So I'm just going to get rid of this job
So I'm just going to get rid of this job skills flat verify that I named job
skills flat verify that I named job skills query verify that I named and
skills query verify that I named and then the group by analysis. From here in
then the group by analysis. From here in the home tab I'm going to navigate into
the home tab I'm going to navigate into transform data and we're going to get
transform data and we're going to get rid of both of these queries of the
rid of both of these queries of the group by by deleting it selecting delete
group by by deleting it selecting delete and then the flat table also of deleting
and then the flat table also of deleting that as well. So now let's get into one
that as well. So now let's get into one of my favorite features inside of Power
of my favorite features inside of Power Query and that's column from example.
Query and that's column from example. We're going to be doing an example.
We're going to be doing an example. We're going to be modifying our job
We're going to be modifying our job postings fact table even further. We're
postings fact table even further. We're going to start simple first. We're going
going to start simple first. We're going to navigate over here to the job posted
to navigate over here to the job posted date column which is actually
date column which is actually incorrectly labeled, right? Should be
incorrectly labeled, right? Should be job posted date time. So say we wanted
job posted date time. So say we wanted to extract the date out of this. You
to extract the date out of this. You already know you can use the transform
already know you can use the transform tab and you could extract out the date
tab and you could extract out the date using this method. We could also use add
using this method. We could also use add column to extract out the date. But the
column to extract out the date. But the main purpose of showing this is under
main purpose of showing this is under add column we also have this of column
add column we also have this of column from example which we're going to be
from example which we're going to be going over in this anyway we want to do
going over in this anyway we want to do this from the selection or in our case
this from the selection or in our case we want to extract out the date and so
we want to extract out the date and so what I can do is just start typing and
what I can do is just start typing and in this case I just put one and a bunch
in this case I just put one and a bunch of different options popped up even more
of different options popped up even more options I'll say than are available in
options I'll say than are available in the popup in the transform and the add
the popup in the transform and the add column tab for just date itself. So
column tab for just date itself. So that's why I recommend this because you
that's why I recommend this because you can get a lot more options out of this.
can get a lot more options out of this. Anyway, I just want to get the date
Anyway, I just want to get the date only. So I'm going to navigate and
only. So I'm going to navigate and select this one right here of 111 2024
select this one right here of 111 2024 and select it. And then whenever I press
and select it. And then whenever I press enter, everything else is going to
enter, everything else is going to autofill in. So what's happened is this
autofill in. So what's happened is this is a light gray because I didn't do an
is a light gray because I didn't do an an example here. And so I know that I
an example here. And so I know that I entered it here. We're going to have
entered it here. We're going to have other ones where we have to enter more
other ones where we have to enter more than one example. Anyway, the reason why
than one example. Anyway, the reason why the name of this lesson is M language is
the name of this lesson is M language is because, well, we need to inspect to
because, well, we need to inspect to make sure that we're doing this
make sure that we're doing this correctly. So, anytime you're doing
correctly. So, anytime you're doing this, you need to look up here under
this, you need to look up here under transform and make sure that this M
transform and make sure that this M language here makes sense of what we're
language here makes sense of what we're trying to do. You don't need to be an
trying to do. You don't need to be an expert at reading it, but we can
expert at reading it, but we can basically see that we're extracting the
basically see that we're extracting the date from job posted date. Okay, that
date from job posted date. Okay, that sounds about right. Sometimes this will
sounds about right. Sometimes this will give you bogus results that aren't what
give you bogus results that aren't what you want. and looking yep up here in
you want. and looking yep up here in this section is going to help you out.
this section is going to help you out. So, I'm good with this. I'm going to go
So, I'm good with this. I'm going to go ahead and click okay. I do want to
ahead and click okay. I do want to change the name of this, but I want it
change the name of this, but I want it to be job posted date. I can't name it
to be job posted date. I can't name it to the same thing. We've seen that
to the same thing. We've seen that before. It gives an error. So, I'm just
before. It gives an error. So, I'm just going to click okay. I want to now take
going to click okay. I want to now take this and I want it next to job posted
this and I want it next to job posted date. So, I'm just going to drag it over
date. So, I'm just going to drag it over here. Now, I'm going to rename this one
here. Now, I'm going to rename this one to job posted date time and then this
to job posted date time and then this one that's date to job posted date. All
one that's date to job posted date. All right, let's do another demo. Maybe this
right, let's do another demo. Maybe this will work out, maybe it won't. This one
will work out, maybe it won't. This one has to do with the job via column.
has to do with the job via column. Remember before we were doing replace
Remember before we were doing replace values to remove that via space. Let's
values to remove that via space. Let's see if we can do this from column from
see if we can do this from column from example. With job via selected, I'm
example. With job via selected, I'm going to go to column from example and
going to go to column from example and then from selection. I only wanted to
then from selection. I only wanted to use this column. Anyway, if I try to
use this column. Anyway, if I try to type in in this case voting reveal.com,
type in in this case voting reveal.com, pretty neat name, and press enter.
pretty neat name, and press enter. Actually surprised. It looks like it
Actually surprised. It looks like it actually did get it correct. Previously
actually did get it correct. Previously it wasn't getting this right and not too
it wasn't getting this right and not too bad. Anyway, inspecting the M language.
bad. Anyway, inspecting the M language. This is doing a transformation and what
This is doing a transformation and what it says is text after delimiter in job
it says is text after delimiter in job via it's looking for a space. So
via it's looking for a space. So basically it's looking for that space in
basically it's looking for that space in there and it's keeping all the values
there and it's keeping all the values after that. And so the case of BB
after that. And so the case of BB Singapore which is multiple values, it
Singapore which is multiple values, it just takes all of it after that first
just takes all of it after that first space. We'll say this is good enough for
space. We'll say this is good enough for our case. I'm going to go ahead and
our case. I'm going to go ahead and click okay. Now that I'm thinking about
click okay. Now that I'm thinking about it, this one I'm going to have to move
it, this one I'm going to have to move over and then also rename. So, we're not
over and then also rename. So, we're not going to end up using this one.
going to end up using this one. Actually, I'm going to go ahead and X
Actually, I'm going to go ahead and X out of that. Instead, I'm just going to
out of that. Instead, I'm just going to select job via, go to transform, replace
select job via, go to transform, replace values, and specifically replace the via
values, and specifically replace the via space with a blank value. And this
space with a blank value. And this cleans it up in only one step. A little
cleans it up in only one step. A little bit easier. All right. Next example I
bit easier. All right. Next example I want to get to. I want to actually be
want to get to. I want to actually be able to combine the salary year average
able to combine the salary year average column with an adjusted value for the
column with an adjusted value for the salary hour average column. Right now
salary hour average column. Right now there's all null values right here.
there's all null values right here. We're going to filter for the time being
We're going to filter for the time being removing blanks while we're doing this
removing blanks while we're doing this just to make it easier for ourel, but
just to make it easier for ourel, but I'm going to delete this step
I'm going to delete this step afterwards. Hope I don't forget. Anyway,
afterwards. Hope I don't forget. Anyway, we can't just combine these columns
we can't just combine these columns because like this case, this is 25 and
because like this case, this is 25 and this is 120,000. we need to adjust this
this is 120,000. we need to adjust this 25 uh first. Now, unfortunately, we're
25 uh first. Now, unfortunately, we're not going to be able to do column from
not going to be able to do column from example for this. We want to multiply
example for this. We want to multiply the salary hour average by a value. So,
the salary hour average by a value. So, that's why thankfully we're smart
that's why thankfully we're smart enough. We've done this already. We can
enough. We've done this already. We can just add a column using multiply.
just add a column using multiply. Specifically, remember we want to
Specifically, remember we want to multiply times 52 weeks in a year times
multiply times 52 weeks in a year times 40 hours in a week, which is 2080. I'm
40 hours in a week, which is 2080. I'm going to click okay. And then for this
going to click okay. And then for this one, right, we don't want to keep the
one, right, we don't want to keep the name multiplication. So inside the
name multiplication. So inside the formula bar, right, we're going to
formula bar, right, we're going to change this name of multiplication to
change this name of multiplication to salary hour adjusted. Clicking enter, we
salary hour adjusted. Clicking enter, we can see that it got updated there. Okay.
can see that it got updated there. Okay. But now that we actually have this
But now that we actually have this column, let's now use as we can see that
column, let's now use as we can see that 25 is transferred into 52,000. We can
25 is transferred into 52,000. We can now combine these two columns because if
now combine these two columns because if you will, they're the same value of the
you will, they're the same value of the same magnitude. Now, so for this one, we
same magnitude. Now, so for this one, we want to have multiple column selections.
want to have multiple column selections. So, holding control, I do salary year
So, holding control, I do salary year average and salary hour average. And I
average and salary hour average. And I come up here to column from example and
come up here to column from example and I select from selection. So, what I'm
I select from selection. So, what I'm going to do is just enter in for this
going to do is just enter in for this one, I want to enter in the 52,000.
one, I want to enter in the 52,000. Pressing enter. It looks like it's
Pressing enter. It looks like it's saying, oh, hey, we want to copy these.
saying, oh, hey, we want to copy these. Oh, but we don't want null for these
Oh, but we don't want null for these values. So, instead, what I'll do is
values. So, instead, what I'll do is I'll click inside of here and I'll start
I'll click inside of here and I'll start entering 120,000. Press enter. See if it
entering 120,000. Press enter. See if it can figure it out. Oh, okay. It did
can figure it out. Oh, okay. It did figure it out. Looking at the M language
figure it out. Looking at the M language for this, we can see that it says, "Hey,
for this, we can see that it says, "Hey, we're just going to combine the text,
we're just going to combine the text, the text from the salary, year average
the text from the salary, year average column and the text from the salary hour
column and the text from the salary hour average column." Notice though that it
average column." Notice though that it is using a text function, which we're
is using a text function, which we're going to have to deal with. Anyway, I'm
going to have to deal with. Anyway, I'm going to go ahead and first change the
going to go ahead and first change the name of this to salary year and hour.
name of this to salary year and hour. Press enter and then press okay. Now,
Press enter and then press okay. Now, like I said, look at these different
like I said, look at these different values. These are italics and to the
values. These are italics and to the right. So I know these are actual number
right. So I know these are actual number values. However, this is to the left
values. However, this is to the left hand side because it converted it to a
hand side because it converted it to a text and I can confirm this underneath
text and I can confirm this underneath the home tab because it says that it's
the home tab because it says that it's text. In our case, we want it to be
text. In our case, we want it to be standard. So we're just going to
standard. So we're just going to transfer it to a decimal number. So what
transfer it to a decimal number. So what I'm going to do is going to close and
I'm going to do is going to close and apply this in a new page called salary
apply this in a new page called salary stats. Let's inspect this new column
stats. Let's inspect this new column that we created. I'm going to draw draw
that we created. I'm going to draw draw in a stack bar chart for this. And from
in a stack bar chart for this. And from that job postings fact table for this
that job postings fact table for this we're going to drag in job title short
we're going to drag in job title short into the y-axis and then our newly
into the y-axis and then our newly created column. Let me expand this over
created column. Let me expand this over salary year and hour aggregating this by
salary year and hour aggregating this by median. Now we can also see in the tool
median. Now we can also see in the tool tips what is the count of all these. So
tips what is the count of all these. So I'm going to drag this into here and
I'm going to drag this into here and select this to count. So with this
select this to count. So with this making this into focus mode, we can now
making this into focus mode, we can now see we're having even more values based
see we're having even more values based on this count and we have more inputs
on this count and we have more inputs into what these different salaries are.
into what these different salaries are. Not just based on only the yearly
Not just based on only the yearly salary, but also the hourly salary. Now,
salary, but also the hourly salary. Now, one more example to use for this column
one more example to use for this column from example. We're going to go back
from example. We're going to go back into transform data. And I did forget a
into transform data. And I did forget a step if you can't remember. It didn't
step if you can't remember. It didn't affect that last visualization, but
affect that last visualization, but remember we did do this filtered rows to
remember we did do this filtered rows to remove those values that didn't have or
remove those values that didn't have or had null values for the salary. We we do
had null values for the salary. We we do want to remove that step. So, I'm going
want to remove that step. So, I'm going to go ahead and delete that. All right.
to go ahead and delete that. All right. And then go move to the last step. All
And then go move to the last step. All right. There's last one last thing I
right. There's last one last thing I want to do and it deals with the salary
want to do and it deals with the salary hour average column. Once again, uh no
hour average column. Once again, uh no uh but I'm only going to filter this
uh but I'm only going to filter this again, but I only want to filter it for
again, but I only want to filter it for hours. So, we can actually see all the
hours. So, we can actually see all the things in here. Once again, this is
things in here. Once again, this is something we'll need to remove with this
something we'll need to remove with this salary hour average column. I want to be
salary hour average column. I want to be able to bucket data. What do I mean by
able to bucket data. What do I mean by that? Well, let's select salary hour
that? Well, let's select salary hour average. Go into add column and do
average. Go into add column and do column from example. I want to put these
column from example. I want to put these salaries into $10 increments. So
salaries into $10 increments. So something like 25. I want it to be 2230.
something like 25. I want it to be 2230. I'm going to press enter. And we can see
I'm going to press enter. And we can see that it filled it in. So in this case,
that it filled it in. So in this case, just going down to make sure we have it.
just going down to make sure we have it. So this case 68.24, it does a bucket of
So this case 68.24, it does a bucket of 60 to 70. Pretty cool. And looking at
60 to 70. Pretty cool. And looking at the M language for this, it actually
the M language for this, it actually goes off screen. It does some sort of
goes off screen. It does some sort of offset and then basically increments by
offset and then basically increments by tens based on the value. Overall,
tens based on the value. Overall, inspecting these different values, it is
inspecting these different values, it is working correctly. So I'm okay with it.
working correctly. So I'm okay with it. I am going to change this name of this
I am going to change this name of this from range to salary hour bucket and
from range to salary hour bucket and then I'm going to click okay. All right.
then I'm going to click okay. All right. So now we have this new one. Once again
So now we have this new one. Once again remember we did filter for just the
remember we did filter for just the hourly data only. I don't want to keep
hourly data only. I don't want to keep that or this step of filtering. So I'm
that or this step of filtering. So I'm going to remove it. All the other steps
going to remove it. All the other steps will update for this. And then I can go
will update for this. And then I can go to home and close it and load it in. And
to home and close it and load it in. And now with this one, I can come in here,
now with this one, I can come in here, insert in a stacked column chart, drag
insert in a stacked column chart, drag salary bucket into the x-axis, and then
salary bucket into the x-axis, and then we want to count that as well. So I'll
we want to count that as well. So I'll drag it into the count of here. And
drag it into the count of here. And entering into focus mode, we can see
entering into focus mode, we can see that some of the most popular salaries
that some of the most popular salaries are between 20 to 30, 67, 40, 50, 50,
are between 20 to 30, 67, 40, 50, 50, and whatnot. So some pretty interesting
and whatnot. So some pretty interesting insights out of bucketing this together.
insights out of bucketing this together. And it basically creates what is known
And it basically creates what is known as like a histogram. Now, you may be
as like a histogram. Now, you may be like, Luke, looking at this, this is out
like, Luke, looking at this, this is out of order because 0 to 10 is all the way
of order because 0 to 10 is all the way back here. I mean, yeah, it is out of
back here. I mean, yeah, it is out of order. The easiest way to fix this,
order. The easiest way to fix this, unfortunately, is using DAX, which
unfortunately, is using DAX, which conveniently is coming up in the next
conveniently is coming up in the next chapter. And so, we will talk about how
chapter. And so, we will talk about how to tackle this problem of sorting it
to tackle this problem of sorting it using that X-axis in this case.
using that X-axis in this case. Now, let's crank up a notch and let's
Now, let's crank up a notch and let's jump into custom columns. With this,
jump into custom columns. With this, we're going to be actually creating or
we're going to be actually creating or writing M language, if you will, in
writing M language, if you will, in order to build these custom columns. For
order to build these custom columns. For this, I wanted to since it's more
this, I wanted to since it's more advanced, I want to keep it familiar
advanced, I want to keep it familiar with what you've done already. So, we're
with what you've done already. So, we're going to be recreating how we created
going to be recreating how we created this salary hour adjusted column and the
this salary hour adjusted column and the salary year and hour column. So, let's
salary year and hour column. So, let's start with the salary hour adjusted
start with the salary hour adjusted first because that one's frankly the
first because that one's frankly the easiest. We're going to go into add
easiest. We're going to go into add column and we're going to select custom
column and we're going to select custom column. In this case, a new pop-up
column. In this case, a new pop-up window comes up called custom column.
window comes up called custom column. You can name the column. So remember,
You can name the column. So remember, we're doing salary, hour, adjusted, and
we're doing salary, hour, adjusted, and I'm going to name this V1. Then
I'm going to name this V1. Then underneath here, we have our custom
underneath here, we have our custom column formula. And we have all our
column formula. And we have all our available columns on the right hand
available columns on the right hand side. So I can take something like
side. So I can take something like salary, hour, average, and insert that
salary, hour, average, and insert that in over here. In this case, if I were to
in over here. In this case, if I were to click okay and load this in, it's going
click okay and load this in, it's going to then load in those values. As I can
to then load in those values. As I can see, 25 here, 25 over here in that
see, 25 here, 25 over here in that salary hour average column. So, that's
salary hour average column. So, that's just a simple way. But navigating back
just a simple way. But navigating back into it by clicking that settings icon,
into it by clicking that settings icon, we can actually do manipulations with
we can actually do manipulations with this. We're not going to do anything
this. We're not going to do anything advanced. Remember before we did
advanced. Remember before we did multiplication, we did 2080. Well, with
multiplication, we did 2080. Well, with 2080, right, is 52 weeks in a year times
2080, right, is 52 weeks in a year times 40 hours in a week. So, whenever I do
40 hours in a week. So, whenever I do this for salary hour adjusted V1, click
this for salary hour adjusted V1, click okay. It now updates from that 25 to
okay. It now updates from that 25 to 52,000, which we can see from this other
52,000, which we can see from this other column that we created already. That is
column that we created already. That is correct. All right. Next task. We want
correct. All right. Next task. We want to recreate this salary, year, and hour
to recreate this salary, year, and hour column. Once again, we're going to go
column. Once again, we're going to go and select custom column and call this
and select custom column and call this salary year and our V1. Now, for this
salary year and our V1. Now, for this one, we need an if statement. Basically,
one, we need an if statement. Basically, we're going to write an if statement and
we're going to write an if statement and then have things below it. I'll be
then have things below it. I'll be honest, I don't have the M language
honest, I don't have the M language memorized for that, and I don't think
memorized for that, and I don't think you need to necessarily, too. Instead,
you need to necessarily, too. Instead, I'd recommend using your favorite
I'd recommend using your favorite chatbot, ChatGBT, or even Google Gemini.
chatbot, ChatGBT, or even Google Gemini. In it, I'm going to provide this prompt.
In it, I'm going to provide this prompt. Give me the custom column code for Power
Give me the custom column code for Power Query 2. Combine the salary year average
Query 2. Combine the salary year average column and salary hour adjusted column.
column and salary hour adjusted column. There's either a value in either one or
There's either a value in either one or the other column. Go ahead and click
the other column. Go ahead and click enter. It gives me this bad boy, which
enter. It gives me this bad boy, which looks pretty simple. I'm going to go
looks pretty simple. I'm going to go ahead and copy this. So, I can just
ahead and copy this. So, I can just select copy. I'm going to go ahead and
select copy. I'm going to go ahead and paste it. I press Ctrl +V. Notice there
paste it. I press Ctrl +V. Notice there are two question marks or sorry, two
are two question marks or sorry, two equal signs. I'm going to remove this.
equal signs. I'm going to remove this. Everything looks like it's okay. It says
Everything looks like it's okay. It says no syntax errors have been detected.
no syntax errors have been detected. I'll click okay. And scrolling here
I'll click okay. And scrolling here through here, we can see that it worked.
through here, we can see that it worked. We have 52,000 here for salary hour
We have 52,000 here for salary hour average. And then for this row that has
average. And then for this row that has salary year average in it, we have a
salary year average in it, we have a value for it. So it's working out. Now,
value for it. So it's working out. Now, if you're not comfortable using the M
if you're not comfortable using the M language for this or using CHBT for it,
language for this or using CHBT for it, no big deal. If we actually inspect this
no big deal. If we actually inspect this current step right here and go into it,
current step right here and go into it, custom code does not actually pop up. It
custom code does not actually pop up. It actually directs us to this of adding a
actually directs us to this of adding a conditional column which we've gone
conditional column which we've gone through and demonstrated before and you
through and demonstrated before and you could have built it similarly using this
could have built it similarly using this instead. I just wanted to demonstrate
instead. I just wanted to demonstrate how to actually use them language.
So now what happens if we want to create a completely new report but I don't want
a completely new report but I don't want frankly I don't want all of these
frankly I don't want all of these different queries in here and I don't
different queries in here and I don't want all these different pages in here.
want all these different pages in here. So, we just want to create a new report
So, we just want to create a new report and specifically I want this job
and specifically I want this job postings fact query as we demonstrate.
postings fact query as we demonstrate. We can go into advanced editor and we
We can go into advanced editor and we can get all this code right here. Well,
can get all this code right here. Well, that's what we're going to use for this.
that's what we're going to use for this. So, let's first start by creating a new
So, let's first start by creating a new report. So, I'm going to start a blank
report. So, I'm going to start a blank report. And in this, I'm going to just
report. And in this, I'm going to just go into transform data. Transform data.
go into transform data. Transform data. And we're going to say this is from a
And we're going to say this is from a new source. Specifically, this is going
new source. Specifically, this is going to be a blank query. We're going to
to be a blank query. We're going to rename this to what we want to move over
rename this to what we want to move over of job postings fact. All right, so
of job postings fact. All right, so let's try this. Navigating back into our
let's try this. Navigating back into our other file. I have the code here that I
other file. I have the code here that I want. I'm going to go ahead and select
want. I'm going to go ahead and select it all and I'm going to press Ctrl C.
it all and I'm going to press Ctrl C. Now, real quick before I paste it, just
Now, real quick before I paste it, just a reminder, right, these are all the
a reminder, right, these are all the different steps, right? We talked about
different steps, right? We talked about earlier. I'm going to go to done. These
earlier. I'm going to go to done. These are all the different steps that are in
are all the different steps that are in the applied step and they're all within
the applied step and they're all within this let statement right there. The last
this let statement right there. The last portion, this in is what's then output
portion, this in is what's then output and it's always basically this last step
and it's always basically this last step right here. So nothing really special
right here. So nothing really special with the syntax further that we need to
with the syntax further that we need to understand about it. Anyway, I did go
understand about it. Anyway, I did go through and actually copy it. Crl + C.
through and actually copy it. Crl + C. Now in inside of our new report going
Now in inside of our new report going into the advanced editor for this one,
into the advanced editor for this one, right? We still have that let there's
right? We still have that let there's nothing for the source and then that
nothing for the source and then that source is that last step. Anyway, I
source is that last step. Anyway, I don't really care about that. I'm going
don't really care about that. I'm going to delete it all and I'm going to paste
to delete it all and I'm going to paste in all of the different code in here.
in all of the different code in here. Now it does say here no syntax errors
Now it does say here no syntax errors have been detected. We are going to run
have been detected. We are going to run into an issue. We'll get to it. But I'm
into an issue. We'll get to it. But I'm going to go ahead and click done. Okay.
going to go ahead and click done. Okay. So in here I am on the last step and it
So in here I am on the last step and it says there's an expression error. the
says there's an expression error. the import star schema file matches no
import star schema file matches no exports. Did you miss a module
exports. Did you miss a module reference? I'm going to say hey go to
reference? I'm going to say hey go to that error and it's going to immediately
that error and it's going to immediately take me to that source step which
take me to that source step which basically says it is this and we're
basically says it is this and we're referencing remember we're referencing
referencing remember we're referencing the source step is referencing the star
the source step is referencing the star schema files query the one that we
schema files query the one that we created about three lessons ago but we
created about three lessons ago but we have no query of star schema files so
have no query of star schema files so let's navigate back to our original file
let's navigate back to our original file here I can see the star schema files is
here I can see the star schema files is right here we can inspect it with
right here we can inspect it with advanced editor and for this one, we're
advanced editor and for this one, we're going to take a little bit of a leap,
going to take a little bit of a leap, but this is the source and it tells us
but this is the source and it tells us the folder and the files that we need to
the folder and the files that we need to connect to. It's just one step. I'm
connect to. It's just one step. I'm going to go ahead and just copy the
going to go ahead and just copy the steps only for this portion and
steps only for this portion and navigating back to our new report. Going
navigating back to our new report. Going into the advanced editor, look at this.
into the advanced editor, look at this. This source up here is referencing that
This source up here is referencing that star schema files. Instead, what I'm
star schema files. Instead, what I'm going to do, I'm going to leave make
going to do, I'm going to leave make sure that that comma is not selected.
sure that that comma is not selected. I'm going to delete it to there. And I'm
I'm going to delete it to there. And I'm going to paste in source, which
going to paste in source, which navigates to the files or folder of this
navigates to the files or folder of this here. And I'm going to click done. And
here. And I'm going to click done. And voila, it loaded in. Now, let's actually
voila, it loaded in. Now, let's actually change this back to what it was, cuz
change this back to what it was, cuz most likely you're not going to know to
most likely you're not going to know to actually change this to this. What's
actually change this to this. What's going to happen is you're going to and
going to happen is you're going to and you're going to run this. This is
you're going to run this. This is probably be the scenario that you're in.
probably be the scenario that you're in. You're going to say, "Hey, go to error."
You're going to say, "Hey, go to error." And you're going to be like, "What the
And you're going to be like, "What the heck is going on here?" Well, this is
heck is going on here?" Well, this is what I recommend doing. or copy this
what I recommend doing. or copy this error message inside your favorite
error message inside your favorite chatbot. Paste this in. Go down and then
chatbot. Paste this in. Go down and then from there, get the actual code itself
from there, get the actual code itself so it knows what's going on. And then
so it knows what's going on. And then pasting that code in there. That's all
pasting that code in there. That's all I'm going to put in here. I'm going to
I'm going to put in here. I'm going to see what it can say. And interesting
see what it can say. And interesting enough, it says the fix for this is we
enough, it says the fix for this is we need to replace this line with the
need to replace this line with the correct folder files function.
correct folder files function. Specifically, this one right here. So,
Specifically, this one right here. So, I'm going to go ahead and copy it, paste
I'm going to go ahead and copy it, paste it into here, and then click done, and
it into here, and then click done, and bam, it got it. So, make sure you're
bam, it got it. So, make sure you're taking advantage of something like chatb
taking advantage of something like chatb and these chatbots anytime you need to
and these chatbots anytime you need to get into some coding, you're not
get into some coding, you're not comfortable with it. Now, one note on
comfortable with it. Now, one note on error troubleshooting. Some of you may
error troubleshooting. Some of you may have executed that previous query and
have executed that previous query and have gotten this error right here where
have gotten this error right here where it says the key didn't match rows in the
it says the key didn't match rows in the table and it specifies well one I'm
table and it specifies well one I'm going to click go to error and I know
going to click go to error and I know it's that second step of navigation
it's that second step of navigation basically says the key isn't right
basically says the key isn't right specifically this folder path most
specifically this folder path most likely this folder path is not correct
likely this folder path is not correct and I know that from troubleshooting
and I know that from troubleshooting this and being experienced with power
this and being experienced with power query but you may not. So, I'm just
query but you may not. So, I'm just going to copy this and then paste it
going to copy this and then paste it into chat GPT to see what it says. And
into chat GPT to see what it says. And it's saying, "Hey, you're getting this
it's saying, "Hey, you're getting this error because either the folder path is
error because either the folder path is incorrect or the file name is
incorrect or the file name is incorrect." So, it's hitting you towards
incorrect." So, it's hitting you towards it. Now, some others of you may be
it. Now, some others of you may be getting this error message. Once again,
getting this error message. Once again, I'll go to error. And this one's with
I'll go to error. And this one's with the second step as well, but this one's
the second step as well, but this one's different. It says, "Hey, data source
different. It says, "Hey, data source not found." It's actually queuing in
not found." It's actually queuing in more to what's wrong with this. And it
more to what's wrong with this. And it has this location here. Anyway, the
has this location here. Anyway, the problem is you probably don't have the
problem is you probably don't have the correct file path of where job postings
correct file path of where job postings fact.csv is. So all you have to do is
fact.csv is. So all you have to do is navigate to where it is in file
navigate to where it is in file explorer. Here I'm in the project folder
explorer. Here I'm in the project folder and navigate into data and then the star
and navigate into data and then the star schema folder. Up here I can just
schema folder. Up here I can just rightclick and say hey I want to copy
rightclick and say hey I want to copy this address. Then inside of chat GBT I
this address. Then inside of chat GBT I can say I found the issue. It was a file
can say I found the issue. It was a file path issue. The file is here. update my
path issue. The file is here. update my code and it update all the different
code and it update all the different code. It has it all here. All I'm going
code. It has it all here. All I'm going to do is just copy it, remove all this
to do is just copy it, remove all this old code in here, paste it in, cross my
old code in here, paste it in, cross my fingers, press done, and bam, it works.
fingers, press done, and bam, it works. So, the moral of the story is don't
So, the moral of the story is don't undervalue using chat GBT and helping
undervalue using chat GBT and helping you troubleshoot things like this. All
you troubleshoot things like this. All right, so that wraps up Power Query. You
right, so that wraps up Power Query. You now have some practice problems to go
now have some practice problems to go through to get more familiar with custom
through to get more familiar with custom columns and also column from example. In
columns and also column from example. In the next lesson, which is going to be
the next lesson, which is going to be the next chapter, we're going to be
the next chapter, we're going to be jumping into DAX. I'm super excited
jumping into DAX. I'm super excited about that. I'll see you there.
Welcome to this fourth and final chapter in this PowerBI course, and we're going
in this PowerBI course, and we're going to be covering DAX or data analysis
to be covering DAX or data analysis expressions. Now, we just got done with
expressions. Now, we just got done with the M language. So, it's very important
the M language. So, it's very important that we distinguish between the two. The
that we distinguish between the two. The M language, which is a more of a
M language, which is a more of a programming language, is used in Power
programming language, is used in Power Query in the process of actually loading
Query in the process of actually loading and transforming the data to get it into
and transforming the data to get it into PowerBI. Whereas, DAX data analysis
PowerBI. Whereas, DAX data analysis expressions is a formula language and
expressions is a formula language and it's used in the front end in PowerBI
it's used in the front end in PowerBI after the data is already loaded in. And
after the data is already loaded in. And in this video, we're going to have an
in this video, we're going to have an intro diving deeper into what exactly
intro diving deeper into what exactly DAX is, but also how we can use it in
DAX is, but also how we can use it in different use cases, specifically with
different use cases, specifically with calculated columns, calculated tables,
calculated columns, calculated tables, and even explicit measures. And then for
and even explicit measures. And then for the remaining two lessons, we're going
the remaining two lessons, we're going to dive deeper into measures, and then
to dive deeper into measures, and then also into parameters. But we're getting
also into parameters. But we're getting ahead of oursel, let's actually look
ahead of oursel, let's actually look into what exactly is DAX.
So what exactly is this formula language? Well, it's a method of
language? Well, it's a method of actually adding calculations to our data
actually adding calculations to our data model that we've loaded into PowerBI.
model that we've loaded into PowerBI. We're going to be focusing only on this
We're going to be focusing only on this tool, but you can actually use DAX and
tool, but you can actually use DAX and other tools as well like Microsoft
other tools as well like Microsoft Excel, Microsoft Fabric, SQL Service
Excel, Microsoft Fabric, SQL Service Analysis, and also Azure Analysis
Analysis, and also Azure Analysis Services. It's basically great at
Services. It's basically great at performing calculations on large sets of
performing calculations on large sets of data. It's super powerful. Now, anytime
data. It's super powerful. Now, anytime you're using some sort of formula
you're using some sort of formula language, I'm going to recommend that
language, I'm going to recommend that you go directly to the data source
you go directly to the data source anytime you have questions. So, I'll put
anytime you have questions. So, I'll put a link up on the screen and feel free to
a link up on the screen and feel free to keep this in a separate window to look
keep this in a separate window to look up any different functions from DAX you
up any different functions from DAX you want to learn more about. Anyway, it has
want to learn more about. Anyway, it has a host of different features. You could
a host of different features. You could use it for aggregation functions such as
use it for aggregation functions such as average, count, max, min, and sum. It
average, count, max, min, and sum. It has date and time functions. Some of
has date and time functions. Some of which we'll demonstrate in this and
which we'll demonstrate in this and actually building a calendar, but more
actually building a calendar, but more ones that you may be familiar with are
ones that you may be familiar with are things like extracting day, minute,
things like extracting day, minute, month. Then they even have things like
month. Then they even have things like logical functions that you can do if
logical functions that you can do if statements and or or. And then finally,
statements and or or. And then finally, other common one that I find myself
other common one that I find myself using is math and trig functions. Now,
using is math and trig functions. Now, if you have familiarity with Excel
if you have familiarity with Excel functions, DAX functions are very
functions, DAX functions are very similar, especially in their syntax they
similar, especially in their syntax they use. The one main thing to get around
use. The one main thing to get around between Excel and DAX is that Excel
between Excel and DAX is that Excel operates in a single cell. Whereas with
operates in a single cell. Whereas with DAX, we can run a calculation that can
DAX, we can run a calculation that can be run not only on a single row within a
be run not only on a single row within a cell, but also entire columns or even
cell, but also entire columns or even tables. I put together this table that
tables. I put together this table that goes through and compares all the
goes through and compares all the different functions. You can access it
different functions. You can access it inside of my course notes. Anyway, the
inside of my course notes. Anyway, the point of it is not to actually have you
point of it is not to actually have you memorize all these different things.
memorize all these different things. Instead, if we were to take a look up
Instead, if we were to take a look up here at the top, we can see that for
here at the top, we can see that for Excel, the sum function that you use
Excel, the sum function that you use here, it's very similar in DAX on sum.
here, it's very similar in DAX on sum. Just instead of an Excel like you'd
Just instead of an Excel like you'd insert in a cell or a range, here in
insert in a cell or a range, here in DAX, you're going to be inserting in
DAX, you're going to be inserting in probably a column name instead. Now I am
probably a column name instead. Now I am making the assumption with building this
making the assumption with building this DAX portion that you have some
DAX portion that you have some familiarity with writing formulas in
familiarity with writing formulas in Excel such as the ones listed here.
Excel such as the ones listed here. Nothing too complex but at least
Nothing too complex but at least understanding the concept of writing
understanding the concept of writing formulas. We're not going to necessarily
formulas. We're not going to necessarily go into the basics of writing formulas.
go into the basics of writing formulas. So unfortunately I'm assuming that you
So unfortunately I'm assuming that you have that kind of knowledge. Now I do
have that kind of knowledge. Now I do want to briefly call out that there is a
want to briefly call out that there is a difference between DAX and M language.
difference between DAX and M language. Like I spoke previously, DAX is a
Like I spoke previously, DAX is a formula language such as sum, average,
formula language such as sum, average, and whatnot. Where the M language is
and whatnot. Where the M language is more of a programming language. It's
more of a programming language. It's much more verbose. What you apply on the
much more verbose. What you apply on the other is not interchangeable with the
other is not interchangeable with the other like Excel functions were. Once
other like Excel functions were. Once again, I put together a table compare
again, I put together a table compare comparing DAX to the M language on
comparing DAX to the M language on certain things. And we can see that it's
certain things. And we can see that it's very much a different type of language
very much a different type of language used for M language. even something like
used for M language. even something like concatenate. Instead, we're going to be
concatenate. Instead, we're going to be using text combined. So, it's not even
using text combined. So, it's not even the same word. It's a different
the same word. It's a different structure. Once again, you don't need to
structure. Once again, you don't need to memorize this list. This is just more
memorize this list. This is just more meant for demonstration purposes. Now,
meant for demonstration purposes. Now, in this chapter, we're going to be
in this chapter, we're going to be focusing on four methods of applying or
focusing on four methods of applying or using DAX inside of PowerBI. And that's
using DAX inside of PowerBI. And that's with measures, specifically explicit
with measures, specifically explicit measures, calculated columns, calculated
measures, calculated columns, calculated tables, and also parameters. Parameters,
tables, and also parameters. Parameters, we're not going to get into an example
we're not going to get into an example of that until the third lesson. Now,
of that until the third lesson. Now, what we're going to be covering during
what we're going to be covering during this chapter is not exclusive of all the
this chapter is not exclusive of all the different DAX locations. You can
different DAX locations. You can actually use it in some other concepts
actually use it in some other concepts as well, such as rowle security, dynamic
as well, such as rowle security, dynamic format strings, and whatnot. Anyway, all
format strings, and whatnot. Anyway, all these concepts listed here are beyond
these concepts listed here are beyond the scope of this course. They're more
the scope of this course. They're more advanced concepts, but once you
advanced concepts, but once you understand the basics of DAX, you'll be
understand the basics of DAX, you'll be able to go in and apply it into these if
able to go in and apply it into these if you decide to learn any of these topics.
So, let's get into our first example with calculated columns. And for this
with calculated columns. And for this and all the examples in this, we're
and all the examples in this, we're going to be continue working from that
going to be continue working from that same file you were working in in the
same file you were working in in the last lesson on the with the M language.
last lesson on the with the M language. But if you didn't happen to keep it, you
But if you didn't happen to keep it, you can just navigate into the project file
can just navigate into the project file and just open up that 3.6 M language
and just open up that 3.6 M language PowerBI file. Inside of here, you should
PowerBI file. Inside of here, you should have that data model with our job
have that data model with our job postings fact table and then our
postings fact table and then our different dimensional tables as shown
different dimensional tables as shown here. Now, inside of PowerBI, we can
here. Now, inside of PowerBI, we can access our use DAX specifically from
access our use DAX specifically from this modeling tab. We're going to be
this modeling tab. We're going to be using all these different features of
using all these different features of new measures, new columns, and new
new measures, new columns, and new table. In this lesson, we'll be using
table. In this lesson, we'll be using new parameter in the third lesson of
new parameter in the third lesson of this. And like I said, rowle security is
this. And like I said, rowle security is beyond the scope of this course. We're
beyond the scope of this course. We're not going to be covering it for this,
not going to be covering it for this, but this is where you'd enter it in. So,
but this is where you'd enter it in. So, here's what I'm thinking for the
here's what I'm thinking for the calculated column. We're going to be
calculated column. We're going to be doing something similar to what we did
doing something similar to what we did in Power Query. Mainly just to
in Power Query. Mainly just to demonstrate how you can do both in each
demonstrate how you can do both in each inside of our job postings fact table.
inside of our job postings fact table. Previously in the last chapter, we use
Previously in the last chapter, we use Power Query to create the salary salary
Power Query to create the salary salary hour adjusted and also salary hour
hour adjusted and also salary hour adjusted V1 column. Both of them just
adjusted V1 column. Both of them just use different methods. Anyway, in this
use different methods. Anyway, in this one, we're going to recreate this column
one, we're going to recreate this column once again, but now using DAX. And then
once again, but now using DAX. And then we'll take it obviously a step further
we'll take it obviously a step further and also build the salary year and hour
and also build the salary year and hour column. But this one's going to be
column. But this one's going to be slightly more complex. Anyway, let's
slightly more complex. Anyway, let's create a new column in this data set. As
create a new column in this data set. As I mentioned, from the report view, you
I mentioned, from the report view, you can get it to it from modeling and
can get it to it from modeling and select new column. The one thing though
select new column. The one thing though is you have to make sure that the
is you have to make sure that the correct table is selected, right? We
correct table is selected, right? We wanted to do job postings fact table.
wanted to do job postings fact table. It's inserting it into company dim. Not
It's inserting it into company dim. Not what I want. I'm just going to press
what I want. I'm just going to press escape. It's going to undo it. So, if
escape. It's going to undo it. So, if you did it from here, make sure you
you did it from here, make sure you select job postings fact and then select
select job postings fact and then select new column to be inserted in here. The
new column to be inserted in here. The other method where you can get to it is
other method where you can get to it is in table view with the appropriate table
in table view with the appropriate table selected. You can see that it appears up
selected. You can see that it appears up at the top as well or you can just
at the top as well or you can just rightclick it and inside the table
rightclick it and inside the table itself select new column. And I like
itself select new column. And I like doing it here from here because it's
doing it here from here because it's showing me visibly what's happening in
showing me visibly what's happening in here. So this is my recommended way of
here. So this is my recommended way of doing it. Anyway, we want to make this
doing it. Anyway, we want to make this salary hour adjusted column. And we can
salary hour adjusted column. And we can see that we start by writing first the
see that we start by writing first the column name before the equal sign. And
column name before the equal sign. And we call the salary hour adjusted V2.
we call the salary hour adjusted V2. Now, as a reminder, we're going to be
Now, as a reminder, we're going to be taking that salary hour average column
taking that salary hour average column and multiplying it times 52 weeks in a
and multiplying it times 52 weeks in a year and 40 hours per week. So, what I
year and 40 hours per week. So, what I can start doing is just typing in this
can start doing is just typing in this column name. And you're noticing that we
column name. And you're noticing that we have this syntax here. It has the table
have this syntax here. It has the table name and then the column name. We want
name and then the column name. We want this one right here of job postings fact
this one right here of job postings fact salary hour average. It's highlighted
salary hour average. It's highlighted blue so I know it's working correctly.
blue so I know it's working correctly. We're just going to do that for the time
We're just going to do that for the time being. Press enter. Make sure that it
being. Press enter. Make sure that it loads in. Okay, we have those values in.
loads in. Okay, we have those values in. Now all we want to do is do some simple
Now all we want to do is do some simple multiplication. So I'll do a time symbol
multiplication. So I'll do a time symbol of 52 weeks in a year and then 40 hours
of 52 weeks in a year and then 40 hours in a week. Press enter and we get that
in a week. Press enter and we get that 520,000. I'm going to go ahead and just
520,000. I'm going to go ahead and just format it as currency. One thing to note
format it as currency. One thing to note over here in the data pane, we can see
over here in the data pane, we can see scrolling on down salary hour adjusted
scrolling on down salary hour adjusted V2 has this special symbol in front of
V2 has this special symbol in front of it symbolizing that it is a calculated
it symbolizing that it is a calculated column. So it cues you into that. Now
column. So it cues you into that. Now let's create this salary year and hour
let's create this salary year and hour V1. I'm going to go ahead and select new
V1. I'm going to go ahead and select new column. Give it the name salary year and
column. Give it the name salary year and hour V2. And now remember this one is
hour V2. And now remember this one is taking whether they have a value in that
taking whether they have a value in that salary year average column right here.
salary year average column right here. It's going to take either this value or
It's going to take either this value or if this is null it's going to end up
if this is null it's going to end up taking our salary hour adjusted. So this
taking our salary hour adjusted. So this value right here. Now I'll be honest
value right here. Now I'll be honest this is more of an advanced technique in
this is more of an advanced technique in order to combine these two columns. So I
order to combine these two columns. So I wouldn't expect you to know this off the
wouldn't expect you to know this off the top of your head. Instead, I'd recommend
top of your head. Instead, I'd recommend you use something like chatgbt and I
you use something like chatgbt and I provide a prompt like this. I'm using
provide a prompt like this. I'm using DAX for calculated columns. I want the
DAX for calculated columns. I want the value in it to be either the the salary
value in it to be either the the salary or average or the salary hour adjusted
or average or the salary hour adjusted V2. Make sure you give the full table
V2. Make sure you give the full table and column name to help it out. And it
and column name to help it out. And it says assume the other well column is
says assume the other well column is null. Go ahead and click enter. It gives
null. Go ahead and click enter. It gives me this formula which is an if formula.
me this formula which is an if formula. I'm going to go ahead and copy this.
I'm going to go ahead and copy this. Notice it has the column name of
Notice it has the column name of preferred salary. I don't want to copy
preferred salary. I don't want to copy that. That's why I didn't copy that.
that. That's why I didn't copy that. Anyway, inside of here, I'm going to go
Anyway, inside of here, I'm going to go ahead and paste that in. And apparently
ahead and paste that in. And apparently I did copy that, so I lied to you. But
I did copy that, so I lied to you. But notice that all of the different there's
notice that all of the different there's no errors or anything like that. I'm
no errors or anything like that. I'm going to go ahead and press enter. See
going to go ahead and press enter. See if it works. And bam, it does. Now, if
if it works. And bam, it does. Now, if you've taken like my Excel course, this
you've taken like my Excel course, this is probably looking very familiar to
is probably looking very familiar to what you've done in my Excel course for
what you've done in my Excel course for making if statements. Once again, we're
making if statements. Once again, we're not going to be going into a lot of this
not going to be going into a lot of this because I just want to stick to the
because I just want to stick to the basics and show you how you can use
basics and show you how you can use something like Chad GBT to help out.
something like Chad GBT to help out. Now, I want to pause real quick and
Now, I want to pause real quick and evaluate because we just showed how to
evaluate because we just showed how to create a calculated column and
create a calculated column and previously we were using custom columns
previously we were using custom columns inside of Power Queries. So, you may be
inside of Power Queries. So, you may be like, Luke, which one should I use? You
like, Luke, which one should I use? You just ran through that calculated columns
just ran through that calculated columns one and did some advanced calculations
one and did some advanced calculations and I have no idea how to do that. Well,
and I have no idea how to do that. Well, the good news is in most cases I'm going
the good news is in most cases I'm going to recommend don't use calculated
to recommend don't use calculated columns. Instead, use your vast
columns. Instead, use your vast knowledge you already have on custom
knowledge you already have on custom columns. Specifically, Power Query is
columns. Specifically, Power Query is much better at data transformations and
much better at data transformations and preparations, and it does this before
preparations, and it does this before the data is even loaded into the model.
the data is even loaded into the model. So, you don't have to do it in the front
So, you don't have to do it in the front end after all this is done. Also, I like
end after all this is done. Also, I like to keep all of my data cleaning in one
to keep all of my data cleaning in one spot, specifically in Power Query. And
spot, specifically in Power Query. And if I start doing in the front end adding
if I start doing in the front end adding these calculators and columns, it gets
these calculators and columns, it gets sort of out of control of understanding
sort of out of control of understanding what was my process to get the data
what was my process to get the data clean and makes it harder to replicate
clean and makes it harder to replicate later. The other thing to note is around
later. The other thing to note is around compression and file sizes. Whenever you
compression and file sizes. Whenever you do this in Power Query, this data is
do this in Power Query, this data is compressed more efficiently and your
compressed more efficiently and your file size is going to be much smaller
file size is going to be much smaller and therefore your data models are going
and therefore your data models are going to load and operate much more quickly.
to load and operate much more quickly. So, long story short, I just showed you
So, long story short, I just showed you calculated columns, so you understood
calculated columns, so you understood you could do them, but I'm going to
you could do them, but I'm going to recommend don't do them.
recommend don't do them. Moving on to the second or third item
Moving on to the second or third item we're going to cover this, and that's
we're going to cover this, and that's calculated tables. It's found under the
calculated tables. It's found under the button of new table. These type of
button of new table. These type of tables are great for creating things
tables are great for creating things like lookup tables, date tables, which
like lookup tables, date tables, which we're going to demonstrate, and also
we're going to demonstrate, and also transforming existing tables. Like I
transforming existing tables. Like I mentioned before, DAX very much not like
mentioned before, DAX very much not like Excel where it operates only a cell. DAX
Excel where it operates only a cell. DAX can operate on column names or a
can operate on column names or a complete table. Now, I will give this
complete table. Now, I will give this caveat to start with because you've
caveat to start with because you've already seen calculated columns. Just
already seen calculated columns. Just like calculated columns and custom
like calculated columns and custom columns, it's much more beneficial to do
columns, it's much more beneficial to do data cleaning and also creating tables
data cleaning and also creating tables in Power Query instead. But I'd be
in Power Query instead. But I'd be remiss if I didn't show you how to
remiss if I didn't show you how to actually do this with DAX in here
actually do this with DAX in here because I think it's a good learning
because I think it's a good learning opportunity. So let's insert a new
opportunity. So let's insert a new table. We can do that by going to the
table. We can do that by going to the table tools here and inserting new
table tools here and inserting new table. Also underneath the report view,
table. Also underneath the report view, we can go into modeling and select new
we can go into modeling and select new table here as well. I like that data
table here as well. I like that data view because I can keep track of what
view because I can keep track of what I'm doing. So I typically like to do it
I'm doing. So I typically like to do it from here and select new table. And it's
from here and select new table. And it's going to show me what I have below here.
going to show me what I have below here. Anyway, let's say for this we want to
Anyway, let's say for this we want to get a table from the job postings fact
get a table from the job postings fact table. Specifically, we want to get a
table. Specifically, we want to get a list of all the different job title
list of all the different job title shorts in here. Remember, we have 10
shorts in here. Remember, we have 10 unique values. This would be more of a
unique values. This would be more of a lookup table example that we're going to
lookup table example that we're going to do. So, I can go to table tools, insert
do. So, I can go to table tools, insert in that new table. For this, we'll call
in that new table. For this, we'll call it job title dim. And then for this,
it job title dim. And then for this, we're going to use a function called
we're going to use a function called distinct. distinct returns a one column
distinct. distinct returns a one column table that contains the distinct values
table that contains the distinct values in a column. So now all we need to do is
in a column. So now all we need to do is specify that column and it's this one
specify that column and it's this one here inside the job postings fact table.
here inside the job postings fact table. I need to make sure that I close off the
I need to make sure that I close off the parentheses and then press enter and
parentheses and then press enter and then bam it generates below. Also I can
then bam it generates below. Also I can see this table inside of here over here
see this table inside of here over here on job title dim. If you notice, this
on job title dim. If you notice, this has a little calculator in front of the
has a little calculator in front of the table icon to show that it's a
table icon to show that it's a calculated table and it shows the one
calculated table and it shows the one icon. Now, let's create a date table, a
icon. Now, let's create a date table, a date dimensional table. For this, we're
date dimensional table. For this, we're going to call this date dim. And we're
going to call this date dim. And we're going to use the calendar function. And
going to use the calendar function. And in this, it returns a table with one
in this, it returns a table with one column of all dates between the start
column of all dates between the start date and end date. I can see the syntax
date and end date. I can see the syntax up here. It's prompting me to put in the
up here. It's prompting me to put in the start date first and then the end date.
start date first and then the end date. Now, these dates do have to be in a
Now, these dates do have to be in a certain format. So, I'm going to use the
certain format. So, I'm going to use the date function specifying 2024 January
date function specifying 2024 January 1st for this. Then putting a comma, we
1st for this. Then putting a comma, we can now see we're in the end date. We're
can now see we're in the end date. We're going to do date as well. And we want to
going to do date as well. And we want to go to the 31st of December for that
go to the 31st of December for that year. And then we need to put a closing
year. And then we need to put a closing parenthesis on all that. Okay, I'm going
parenthesis on all that. Okay, I'm going to go ahead and press enter. All right,
to go ahead and press enter. All right, so pretty neat. This goes through and
so pretty neat. This goes through and creates a date automatically to the end.
creates a date automatically to the end. And I'm realizing now that I have a
And I'm realizing now that I have a typo. I put in 32. I didn't even know
typo. I put in 32. I didn't even know that was possible. Uh, going ahead and
that was possible. Uh, going ahead and run enter. It did go ahead and clean
run enter. It did go ahead and clean that up. That's why it's always good
that up. That's why it's always good that you inspect your data. Now, because
that you inspect your data. Now, because this is going to be we're actually we're
this is going to be we're actually we're going to keep this date dim for the
going to keep this date dim for the remainder of the course. And this is
remainder of the course. And this is going to be our reference date table
going to be our reference date table that we can use. We want to go ahead and
that we can use. We want to go ahead and mark this as a date table up here under
mark this as a date table up here under tables tools. This will enable the
tables tools. This will enable the creation of date related visuals, tables
creation of date related visuals, tables and quick measures using the tables date
and quick measures using the tables date data. So this is really powerful to make
data. So this is really powerful to make some automatic features actually happen
some automatic features actually happen in the back end. For this we need to
in the back end. For this we need to choose the correct column and there's
choose the correct column and there's only one column in here. It's date. It's
only one column in here. It's date. It's validated successfully. We'll go ahead
validated successfully. We'll go ahead and click save. With this I'm going to
and click save. With this I'm going to now ma uh navigate over to the model
now ma uh navigate over to the model view and we can see over here we have
view and we can see over here we have our job title dim table and our date
our job title dim table and our date dim. We're not going to use our job
dim. We're not going to use our job title dim anymore. So, I'm not going to
title dim anymore. So, I'm not going to connect it in, but I will drag date dim
connect it in, but I will drag date dim over here. And for this, I'll drag date
over here. And for this, I'll drag date onto job posted date. So, we can create
onto job posted date. So, we can create this relationship. And it's picking up
this relationship. And it's picking up that. Okay. The date, job posted date.
that. Okay. The date, job posted date. It's a one to many relationship, right?
It's a one to many relationship, right? There's only one unique value in the
There's only one unique value in the date table. And there's going to be
date table. And there's going to be multiple in the job postings fact.
multiple in the job postings fact. Crossfit direction we'll leave as single
Crossfit direction we'll leave as single right now. Click save. And this
right now. Click save. And this relationship is established. Now, let's
relationship is established. Now, let's get into modifying this date table even
get into modifying this date table even further. I lied to you a little bit in
further. I lied to you a little bit in the fact that we typed this out and I
the fact that we typed this out and I did that so that way you understand
did that so that way you understand understood that that could be a way of
understood that that could be a way of doing it. But if I type out calendar,
doing it. But if I type out calendar, there's actually this other one called
there's actually this other one called calendar auto. And inside of here, I
calendar auto. And inside of here, I notic in the the parameter is actually a
notic in the the parameter is actually a optional because it's in brackets. So,
optional because it's in brackets. So, you don't have to actually insert
you don't have to actually insert anything into here. and from it array it
anything into here. and from it array it returns a table with one column of dates
returns a table with one column of dates calculated from the model automatically
calculated from the model automatically and we're connected into the model. So
and we're connected into the model. So now when I run it it did I did run it
now when I run it it did I did run it there's no no difference because it
there's no no difference because it automatically picks up those dates from
automatically picks up those dates from January 1st all the way to December 31st
January 1st all the way to December 31st and I don't have to specify it. Also if
and I don't have to specify it. Also if we add more dates in this would be more
we add more dates in this would be more preferential because then we don't have
preferential because then we don't have to go in and try to update the dates and
to go in and try to update the dates and just using the calendar only function.
just using the calendar only function. Now, I do want to crank this up in a
Now, I do want to crank this up in a little bit more. Specifically, I want
little bit more. Specifically, I want more columns than just this. I don't
more columns than just this. I don't want just date. Maybe I want things like
want just date. Maybe I want things like year or day of week. So, what I'm going
year or day of week. So, what I'm going to do is press shift enter to move this
to do is press shift enter to move this on down. And I'm actually going to move
on down. And I'm actually going to move it down twice. And we're going to use
it down twice. And we're going to use the function of add columns. And it
the function of add columns. And it returns a table with new columns
returns a table with new columns specified by the DAX expression. The
specified by the DAX expression. The first expression that we need to put in
first expression that we need to put in is a table and calendar auto is that
is a table and calendar auto is that table. After calendar auto, we need to
table. After calendar auto, we need to insert in a name. It says name one,
insert in a name. It says name one, expression one. Name one is the column
expression one. Name one is the column name. Expression one is the column we
name. Expression one is the column we want to create. Now I'm going press
want to create. Now I'm going press shift and enter on down to the next line
shift and enter on down to the next line to actually do this. We're going to keep
to actually do this. We're going to keep it simple. We want a column called year.
it simple. We want a column called year. So, what function do you think we're
So, what function do you think we're going to use to get the year? Well, we
going to use to get the year? Well, we use year. And inside of here, we need to
use year. And inside of here, we need to specify a date. And so, we need to
specify a date. And so, we need to insert in the column. If I just do a
insert in the column. If I just do a square brackets open up, I can see that
square brackets open up, I can see that date pops up. It's already picking up
date pops up. It's already picking up date because that's the column. Date is
date because that's the column. Date is this column right here. All right. And
this column right here. All right. And then I'm going to close the parenthesis
then I'm going to close the parenthesis on this, right? Because we did the
on this, right? Because we did the table, we did name one, and we did
table, we did name one, and we did expression one. Going ahead and press
expression one. Going ahead and press enter. Now we have year. Now we can
enter. Now we have year. Now we can actually add in even additional things
actually add in even additional things inside of here. I can press comma. I'm
inside of here. I can press comma. I'm going to just shift down, enter down.
going to just shift down, enter down. I'm doing this all the shift enter stuff
I'm doing this all the shift enter stuff just to reformat it. It really doesn't
just to reformat it. It really doesn't matter. This is just so visually we can
matter. This is just so visually we can see the how things are aligned easier
see the how things are aligned easier for me to read it. Anyway, now I'm
for me to read it. Anyway, now I'm seeing we have name two and expression
seeing we have name two and expression two. If I wanted to, I could put in
two. If I wanted to, I could put in something like month number. And as you
something like month number. And as you guessed, I'd probably use a function
guessed, I'd probably use a function called month for this. It takes the
called month for this. It takes the argument of date. So I'll do that square
argument of date. So I'll do that square bracket, insert in date, and then that
bracket, insert in date, and then that is our second expression. So I'll shift
is our second expression. So I'll shift on down and put a closing parenthesis on
on down and put a closing parenthesis on here. Press enter. Bam. We got month
here. Press enter. Bam. We got month number. Since we have month number, you
number. Since we have month number, you know, we're going to need month name. So
know, we're going to need month name. So let's add this in. I'm going to insert
let's add this in. I'm going to insert in a comma and shift enter down. Write
in a comma and shift enter down. Write the month name for this. And for this,
the month name for this. And for this, there's not a month function for this.
there's not a month function for this. For this one, going to the source
For this one, going to the source documentation, we can use the format
documentation, we can use the format function. In it, it takes a value. So,
function. In it, it takes a value. So, in our case, we're going to take date
in our case, we're going to take date and then how we want to format it or the
and then how we want to format it or the format string. We can see that it works
format string. We can see that it works in calculated columns and calculated
in calculated columns and calculated tables as we're doing. Now, if we scroll
tables as we're doing. Now, if we scroll on down, we can get to this section on
on down, we can get to this section on custom datetime formats. And scrolling
custom datetime formats. And scrolling through this as well, I can see that
through this as well, I can see that right here. If we do four lowercase M's
right here. If we do four lowercase M's or uppercase M's, it displays the month
or uppercase M's, it displays the month as a full month name. So inside of here,
as a full month name. So inside of here, I'm going to do format because that's
I'm going to do format because that's the function we want to use. For the
the function we want to use. For the value, we're going to insert in the
value, we're going to insert in the date. And then for the format, inside of
date. And then for the format, inside of quotes, we're going to insert in those
quotes, we're going to insert in those M's. This looks good to me. I'm going to
M's. This looks good to me. I'm going to go ahead and press enter. Bam. We got a
go ahead and press enter. Bam. We got a month name now. So now that we know that
month name now. So now that we know that tactic, if I wanted to do something like
tactic, if I wanted to do something like in the weekday name, I could do similar
in the weekday name, I could do similar with the format and just do four
with the format and just do four lowercase D's running enter. I get the
lowercase D's running enter. I get the weekday name. Now I'm going to enter in
weekday name. Now I'm going to enter in a few more different columns that I want
a few more different columns that I want in there and then we're going to go
in there and then we're going to go through it briefly. First up is date
through it briefly. First up is date key. And all this is doing is just
key. And all this is doing is just getting it into a numerical way. If I
getting it into a numerical way. If I want to manipulate or reference it
want to manipulate or reference it later, I can. Pretty common to use a
later, I can. Pretty common to use a date key in a date dimension table. As
date key in a date dimension table. As we had previously, we're going to keep
we had previously, we're going to keep the year, also the month number, and the
the year, also the month number, and the month name. We'll take it a step further
month name. We'll take it a step further by adding in the year month, which all
by adding in the year month, which all it is in this case is a dash between the
it is in this case is a dash between the two. And then also adding in the quarter
two. And then also adding in the quarter itself. If you notice these, I used all
itself. If you notice these, I used all uppercase. You can use uppercase or
uppercase. You can use uppercase or lowercase when specifying inside of that
lowercase when specifying inside of that format function. Now, jumping to the
format function. Now, jumping to the last one, we did have the weekday name.
last one, we did have the weekday name. And because of that, I included these
And because of that, I included these two extra functions of week number and
two extra functions of week number and weekday number. All they take is the fun
weekday number. All they take is the fun function for this one, week number of
function for this one, week number of actual week num specifying the date and
actual week num specifying the date and then the number two. Same thing for
then the number two. Same thing for weekday. It takes the date and then the
weekday. It takes the date and then the number two. for both of these options
number two. for both of these options where we're specifying two. In this
where we're specifying two. In this case, I'm at the weak gnome
case, I'm at the weak gnome documentation syntax is date and then in
documentation syntax is date and then in these brackets here, it's saying it's an
these brackets here, it's saying it's an optional parameter, the return type. And
optional parameter, the return type. And if we go scroll down to this table, we
if we go scroll down to this table, we can see that by default, it's one and
can see that by default, it's one and that means the week begins on Sunday.
that means the week begins on Sunday. I'm fancymancy and I changed two so that
I'm fancymancy and I changed two so that way the week begins on a Monday cuz
way the week begins on a Monday cuz that's when the work week begins. So, I
that's when the work week begins. So, I could easily take this two out if I
could easily take this two out if I wanted to, as I mentioned, and run this
wanted to, as I mentioned, and run this again. And this doesn't really change
again. And this doesn't really change any of our different values. It's going
any of our different values. It's going to change it later on when we go to plot
to change it later on when we go to plot it. Anyway, this is our date dimensional
it. Anyway, this is our date dimensional table. Feel free to pause the screen and
table. Feel free to pause the screen and make sure that you get this down into
make sure that you get this down into your report so you have this available.
your report so you have this available. Now, I love having this dateimensional
Now, I love having this dateimensional table because not only now I can do
table because not only now I can do something like this where I can take the
something like this where I can take the line chart and drag our date into the
line chart and drag our date into the x-axis and then job ID into the yaxis
x-axis and then job ID into the yaxis for the count. Okay, so we get that.
for the count. Okay, so we get that. We've seen that before, but we can now
We've seen that before, but we can now take it a step for f further with our
take it a step for f further with our date dimensional table. In this, I'm
date dimensional table. In this, I'm going to create a stacked column chart.
going to create a stacked column chart. And I can drag the weekday name into the
And I can drag the weekday name into the X axis and drag the job ID into the
X axis and drag the job ID into the Yaxis. And we can see out of this, we'll
Yaxis. And we can see out of this, we'll go into focus mode. Tuesday is by far
go into focus mode. Tuesday is by far the most postings that when they happen
the most postings that when they happen and they happen the least on the
and they happen the least on the weekend. Now, you may be like, Luke,
weekend. Now, you may be like, Luke, this is great and all, but these names,
this is great and all, but these names, these weekday names are out of order.
these weekday names are out of order. What the heck is going on here? I want
What the heck is going on here? I want them to be in order. Well, navigating
them to be in order. Well, navigating back into that table view for our column
back into that table view for our column or for our date table itself. What we
or for our date table itself. What we can do is you can just select your
can do is you can just select your column of choice. In this case, weekday
column of choice. In this case, weekday name, we want it to we want to organize
name, we want it to we want to organize it. And inside this column tools tab
it. And inside this column tools tab that's going to pop up when we have this
that's going to pop up when we have this selected, they have this option all the
selected, they have this option all the way to the right of sort by column. and
way to the right of sort by column. and you sort one column by the contents of
you sort one column by the contents of another. Luckily, we built this this
another. Luckily, we built this this weekday number which we can see that the
weekday number which we can see that the one value is associated with Sunday, two
one value is associated with Sunday, two with Monday and so on. Anyway, what we
with Monday and so on. Anyway, what we can do is select sort by column with
can do is select sort by column with weekday name selected. We can say sort
weekday name selected. We can say sort by the week number. Now, you may get
by the week number. Now, you may get this popup right here that says sort by
this popup right here that says sort by another column. We can't sort the
another column. We can't sort the weekday name column by week number. This
weekday name column by week number. This I feel is a little bit of a glitch right
I feel is a little bit of a glitch right now in PowerBI. I'm going to click
now in PowerBI. I'm going to click close. And what you may need to do is
close. And what you may need to do is just recclick it, go to sort by column,
just recclick it, go to sort by column, and just do it again. Select it's a
and just do it again. Select it's a weekday number. And then this popup
weekday number. And then this popup doesn't happen anymore. I don't know.
doesn't happen anymore. I don't know. It's just a weird little glitch that's
It's just a weird little glitch that's going on with PowerBI. Anyway, I go back
going on with PowerBI. Anyway, I go back to report view. I need to actually
to report view. I need to actually refresh this and go back here. I'm going
refresh this and go back here. I'm going to remove weekday name and drag weekday
to remove weekday name and drag weekday name back into the X-axis. All right.
name back into the X-axis. All right. Bam. It has now updated to be in order
Bam. It has now updated to be in order from Sunday down to Saturday. Now, as I
from Sunday down to Saturday. Now, as I mentioned, I like my work week to start
mentioned, I like my work week to start on Monday. So, actually, I'm going to go
on Monday. So, actually, I'm going to go back into that table view, and we're
back into that table view, and we're going to change that week number for the
going to change that week number for the weekday function to specify that we want
weekday function to specify that we want it to begin on Monday. And I'll do the
it to begin on Monday. And I'll do the same thing for week number itself.
same thing for week number itself. Specifying this is two. Then running
Specifying this is two. Then running this all, pressing enter. I can see now
this all, pressing enter. I can see now that it's updated because Monday up here
that it's updated because Monday up here is now one. And navigating back to my
is now one. And navigating back to my visual, my visual now updates for that.
visual, my visual now updates for that. Okay, this date dimensional table that
Okay, this date dimensional table that we created is going to be continued to
we created is going to be continued to use for the remainder of the course. So
use for the remainder of the course. So very important that you have this down
very important that you have this down correct. If you need to pause the screen
correct. If you need to pause the screen right now and get this updated formula
right now and get this updated formula for you to actually use.
Now let's jump into the last use case of DAX and it's going to be the m the
DAX and it's going to be the m the primary focus for the next lesson and
primary focus for the next lesson and that's on measures. As you recall from
that's on measures. As you recall from previously anytime we were creating some
previously anytime we were creating some sort of bar chart or count I would drag
sort of bar chart or count I would drag the job title short into that Y-axis and
the job title short into that Y-axis and then anytime I want to do a count of the
then anytime I want to do a count of the jobs to drag that into the X-axis and
jobs to drag that into the X-axis and get the count of this. We also did this
get the count of this. We also did this with job ID as well getting the count
with job ID as well getting the count values are still the same. Anyway, every
values are still the same. Anyway, every single time I had to go through and then
single time I had to go through and then update this title to job count, it's a
update this title to job count, it's a mess. This is what we call an implicit
mess. This is what we call an implicit measure. It's implied. And we're limited
measure. It's implied. And we're limited with these implicit measures to only the
with these implicit measures to only the selections through this drop down arrow
selections through this drop down arrow right here. But we can use explicit
right here. But we can use explicit measures with DAX to make even more
measures with DAX to make even more complex type of measures. But let's keep
complex type of measures. But let's keep it simple for the time being. I'm going
it simple for the time being. I'm going to go ahead and just copy this
to go ahead and just copy this visualization and then paste it on over
visualization and then paste it on over here. And we'll get rid of this job
here. And we'll get rid of this job count. That's what we're going to be
count. That's what we're going to be creating, a count of the jobs. Now, to
creating, a count of the jobs. Now, to create a measure, we can do it a number
create a measure, we can do it a number of different ways. I can rightclick the
of different ways. I can rightclick the job postings fact table and then say,
job postings fact table and then say, hey, I want to create a new measure. We
hey, I want to create a new measure. We can navigate to it under the modeling
can navigate to it under the modeling tab, getting to this new measure. Also,
tab, getting to this new measure. Also, I can just select the table itself and
I can just select the table itself and table tools pops up. And then from there
table tools pops up. And then from there create new measure. So we first start by
create new measure. So we first start by giving this measure a name. We're going
giving this measure a name. We're going to keep it simple of job count. And we
to keep it simple of job count. And we want to do a count. So there's probably
want to do a count. So there's probably a formula called count. And in it we
a formula called count. And in it we need to count the numbers in a column.
need to count the numbers in a column. So we can just specify the job ID. Put a
So we can just specify the job ID. Put a closing parenthesis on this. Press
closing parenthesis on this. Press enter. And now inside of our job
enter. And now inside of our job postings fact table we have this
postings fact table we have this measure. We can see this by this little
measure. We can see this by this little calculator icon. And I can take job
calculator icon. And I can take job count which has that name written. And
count which has that name written. And so the column name is also updated for
so the column name is also updated for job count. And we're getting that same
job count. And we're getting that same value of 128994 as we got with the
value of 128994 as we got with the implicit measure. So their explicit
implicit measure. So their explicit measure a lot easier. So every time now
measure a lot easier. So every time now we want job count. All we got to do is
we want job count. All we got to do is drag in that explicit measure. Now job
drag in that explicit measure. Now job count just because it's in the job
count just because it's in the job postings f fact table doesn't mean it
postings f fact table doesn't mean it can only be used with the job postings
can only be used with the job postings fact table. Remember we do have
fact table. Remember we do have relationships throughout the tables. So,
relationships throughout the tables. So, we could technically use this for skills
we could technically use this for skills to figure out what are the counts of
to figure out what are the counts of jobs for a certain skill. Back in our
jobs for a certain skill. Back in our report view, I'm going to get rid of
report view, I'm going to get rid of this table right here. We don't need
this table right here. We don't need this one anymore since we have an
this one anymore since we have an explicit measure. Now, I'm going to copy
explicit measure. Now, I'm going to copy it and then paste it on over here. And
it and then paste it on over here. And instead of job title short in the yaxis,
instead of job title short in the yaxis, I'm going to navigate to that skills dim
I'm going to navigate to that skills dim and I'm going to drag skills over to the
and I'm going to drag skills over to the Yaxis. Going into focus mode because we
Yaxis. Going into focus mode because we can see that the visualization built.
can see that the visualization built. Bam. We're now getting this job count
Bam. We're now getting this job count based on the skill. Let's just create
based on the skill. Let's just create one more measure for funsies and that's
one more measure for funsies and that's going to be I'm going to rightclick this
going to be I'm going to rightclick this and select new measure for this.
and select new measure for this. Remember we were doing the median yearly
Remember we were doing the median yearly salary all the time with this. Well, we
salary all the time with this. Well, we can create a measure for this. I'm going
can create a measure for this. I'm going to create median yearly salary. Set it
to create median yearly salary. Set it to equal. And then in this we're going
to equal. And then in this we're going to use the median function and we're
to use the median function and we're going to specify that salary year
going to specify that salary year average column. Going to close the
average column. Going to close the parenthesis. Press enter. And then how
parenthesis. Press enter. And then how we did that job count for job title
we did that job count for job title short. Well, I can just trade out those
short. Well, I can just trade out those values removing job count. And now we
values removing job count. And now we have the median yearly salary in here.
have the median yearly salary in here. Oh, and if remember right, we had to
Oh, and if remember right, we had to format this every single time with this.
format this every single time with this. If I select median yearly salary uh from
If I select median yearly salary uh from the data pane here and then this measure
the data pane here and then this measure tools pops up. What I can do is I can
tools pops up. What I can do is I can not only change the name but also I can
not only change the name but also I can change what is the format. Specifically,
change what is the format. Specifically, I'm going to change it to currency and
I'm going to change it to currency and zero. And so now, every time I'm using
zero. And so now, every time I'm using this, so let's uh it's going to use that
this, so let's uh it's going to use that same value. Specifically, going to that
same value. Specifically, going to that skills, I'm going to get rid of that job
skills, I'm going to get rid of that job count and drag median yearly salary into
count and drag median yearly salary into here. And whenever I scroll over it,
here. And whenever I scroll over it, it's actually formatted correctly. So,
it's actually formatted correctly. So, not only do I get the correct name, I
not only do I get the correct name, I don't have to update, but it keeps the
don't have to update, but it keeps the data format that I'll want. I love
data format that I'll want. I love explicit measures.
Now, one last thing, I promise, and this has to do with measures versus
has to do with measures versus calculated columns and tables. This is
calculated columns and tables. This is definitely a new concept, especially to
definitely a new concept, especially to those that haven't dealt with measures
those that haven't dealt with measures before. So, it's hard to wrap your head
before. So, it's hard to wrap your head around what's the difference between a
around what's the difference between a calculated column and what is a measure.
calculated column and what is a measure. It's important to understand that for
It's important to understand that for calculated columns and also tables
calculated columns and also tables they're calculated immediately upon data
they're calculated immediately upon data import and they're visible in the data
import and they're visible in the data and also those report views. Now
and also those report views. Now measures on the other hand are not done
measures on the other hand are not done on the data import instead they're done
on the data import instead they're done at query runtime is is when that
at query runtime is is when that basically the visualization is getting
basically the visualization is getting built. So in this case there's a table
built. So in this case there's a table that we're doing on job count. So these
that we're doing on job count. So these job titles it's getting calculated then
job titles it's getting calculated then and it's getting calculated down to that
and it's getting calculated down to that job title level. That's basically the
job title level. That's basically the filter for it. It's available in report
filter for it. It's available in report views like we can do on a canvas, but
views like we can do on a canvas, but it's also available in a DAX view as
it's also available in a DAX view as well. And DAX query view, we'll cover
well. And DAX query view, we'll cover more in the next lesson. I feel like
more in the next lesson. I feel like we've covered enough for the time being.
we've covered enough for the time being. Anyway, it's just an important concept
Anyway, it's just an important concept to understand because many people when
to understand because many people when they go to the table view specifically
they go to the table view specifically for job postings, the fact table that we
for job postings, the fact table that we have here, I can see inside of here
have here, I can see inside of here these calculated columns that we created
these calculated columns that we created of salary hour adjusted and salary year
of salary hour adjusted and salary year and hour as designated by these two
and hour as designated by these two icons in front of it. But if I try to
icons in front of it. But if I try to look for things like the job count or
look for things like the job count or the median yearly salary, that's not
the median yearly salary, that's not going to be anywhere on this table
going to be anywhere on this table because that's not calculated to show in
because that's not calculated to show in this view immediately on the data load.
this view immediately on the data load. Instead, it's not calculated until let's
Instead, it's not calculated until let's say we put a M matrix in here and I draw
say we put a M matrix in here and I draw job title short into the rows and then
job title short into the rows and then job count into the values. It's not
job count into the values. It's not calculated until this time. And it
calculated until this time. And it allows us to get this aggregation at
allows us to get this aggregation at this type of level which we're going to
this type of level which we're going to dive into more in the next lesson. All
dive into more in the next lesson. All right, you have some practice problems
right, you have some practice problems now. Go through and get familiar with
now. Go through and get familiar with calculated columns, calculated tables,
calculated columns, calculated tables, and also these explicit measures. In the
and also these explicit measures. In the next lesson, once you have that all
next lesson, once you have that all down, we're going to be diving even
down, we're going to be diving even deeper into explicit measures because
deeper into explicit measures because they're the primary one that I'm using
they're the primary one that I'm using with DAX in here. With that, I'll see
with DAX in here. With that, I'll see you there.
Welcome to the second of three lessons on DAX. This one is going to be diving
on DAX. This one is going to be diving even deeper into explicit measures. With
even deeper into explicit measures. With this, we're going to dive into building
this, we're going to dive into building more complex measures, but also better
more complex measures, but also better understanding how to use them.
understanding how to use them. Specifically, we're going to be able to
Specifically, we're going to be able to do calculations that we haven't been
do calculations that we haven't been able to do before, like calculating how
able to do before, like calculating how many skills or an allen are associated
many skills or an allen are associated with a particular job title. And because
with a particular job title. And because of this measure, we'll also be able to
of this measure, we'll also be able to look into see do jobs that request more
look into see do jobs that request more skills, do they actually pay more? So,
skills, do they actually pay more? So, some really unique insights that we
some really unique insights that we wouldn't be able to do without DAX and
wouldn't be able to do without DAX and specifically explicit measures. All
specifically explicit measures. All right, let's jump into it.
For this, you can either start with working with that report that you had
working with that report that you had from the last lesson, or if you didn't
from the last lesson, or if you didn't follow along and didn't keep up, feel
follow along and didn't keep up, feel free to just open up the one from the
free to just open up the one from the last lesson on 4.1 DAX intro. I did a
last lesson on 4.1 DAX intro. I did a few more calculations in here for the
few more calculations in here for the column check, the table check, and the
column check, the table check, and the measure check. Anyway, there's um
measure check. Anyway, there's um unnecessary things that we created that
unnecessary things that we created that we're not going to be using later on.
we're not going to be using later on. So, I want to go ahead and clean this
So, I want to go ahead and clean this report up to make sure that it's as
report up to make sure that it's as minimal as necessary so it doesn't cause
minimal as necessary so it doesn't cause issues later on when we're trying to
issues later on when we're trying to build our project. Specifically, I'm
build our project. Specifically, I'm going to delete these two columns. This
going to delete these two columns. This one here on new column check and delete
one here on new column check and delete this one here on date table check. What
this one here on date table check. What I am keeping are the visualizations that
I am keeping are the visualizations that we created in the last one. You may have
we created in the last one. You may have to if you keeping if you're working on
to if you keeping if you're working on from the last lesson, you may have to
from the last lesson, you may have to recreate some of these. But basically we
recreate some of these. But basically we have on the left hand side what are the
have on the left hand side what are the counts of different jobs and what are
counts of different jobs and what are the salaries for different jobs and then
the salaries for different jobs and then conversely we have what are the counts
conversely we have what are the counts of different skills along with what are
of different skills along with what are the different pays for the top paying
the different pays for the top paying skills. So the report itself is looking
skills. So the report itself is looking good. Now let's move over to the data
good. Now let's move over to the data model itself. We did create this job
model itself. We did create this job title dim table which we can view here
title dim table which we can view here inside of our table view. We're not
inside of our table view. We're not going to be using this any further. So,
going to be using this any further. So, I'm going to go ahead and rightclick
I'm going to go ahead and rightclick this and say delete from model. It'll
this and say delete from model. It'll prompt you if you want to do it. Yep.
prompt you if you want to do it. Yep. Next up, after the calculated table we
Next up, after the calculated table we created, I also want to get rid of these
created, I also want to get rid of these calculated columns that we created. So,
calculated columns that we created. So, I want to remove these two columns right
I want to remove these two columns right here. Conveniently, I can see them with
here. Conveniently, I can see them with their icon that there were the
their icon that there were the calculated columns. All you have to do
calculated columns. All you have to do is just rightclick them and say delete
is just rightclick them and say delete from model and confirm it. I'll do it
from model and confirm it. I'll do it again for salary, hour, year. There's a
again for salary, hour, year. There's a error right now cuz I deleted them out
error right now cuz I deleted them out of order. Anyway, both of them gone now.
of order. Anyway, both of them gone now. Now I also want to get rid of salary
Now I also want to get rid of salary hour adjusted and salary year and hour.
hour adjusted and salary year and hour. You can rightclick it and delete it this
You can rightclick it and delete it this way. I want to control it though in
way. I want to control it though in Power Query because remember we did
Power Query because remember we did create these in Power Query. So for this
create these in Power Query. So for this I'm going to go into Power Query by
I'm going to go into Power Query by going to transform data and then inside
going to transform data and then inside of here I'm going to remove these last
of here I'm going to remove these last two steps of adding the different
two steps of adding the different columns into here. And we'll keep
columns into here. And we'll keep everything else in there. Looks good. Go
everything else in there. Looks good. Go ahead and close and apply it. All right.
ahead and close and apply it. All right. Not too bad. We've now cleaned up not
Not too bad. We've now cleaned up not only our report canvas, but also cleaned
only our report canvas, but also cleaned up our data model itself. That's in a
up our data model itself. That's in a good spot to continue on. This is good
good spot to continue on. This is good practice always to get rid of any
practice always to get rid of any measures, calculated columns, or whatnot
measures, calculated columns, or whatnot that you're not using and that aren't
that you're not using and that aren't useful because it's just going to cause
useful because it's just going to cause confusion.
On the same note of doing a model and report cleanup, we also need to make
report cleanup, we also need to make sure that we're implementing best
sure that we're implementing best practices for DAX and measures
practices for DAX and measures specifically in order to organize these
specifically in order to organize these measures that we're creating.
measures that we're creating. Previously, we created these measures
Previously, we created these measures under this job posting fact. And I can
under this job posting fact. And I can see have job count here and median
see have job count here and median yearly salary down below it. It's best
yearly salary down below it. It's best practice to create a table to just keep
practice to create a table to just keep all of your measures in. And we can do
all of your measures in. And we can do this with calculated tables. going to
this with calculated tables. going to modeling, inserting in a new table.
modeling, inserting in a new table. Inside of here, I'm going to rename
Inside of here, I'm going to rename table, and I'm going to do underscore
table, and I'm going to do underscore measures. This is for a few reasons.
measures. This is for a few reasons. One, measures, the actual name is
One, measures, the actual name is reserved. You can't use that. But two,
reserved. You can't use that. But two, since we have an underscore at the
since we have an underscore at the front, this allows it to be up at the
front, this allows it to be up at the top and so we can quickly access any
top and so we can quickly access any measures that are inside of here. Now,
measures that are inside of here. Now, we want to get our two measures that we
we want to get our two measures that we created inside of here. You
created inside of here. You unfortunately you can't just drag and
unfortunately you can't just drag and drop into here. But what I can do is I
drop into here. But what I can do is I can select job count and measure tools
can select job count and measure tools tab comes up and it says the name of it
tab comes up and it says the name of it but also what's the home table and we
but also what's the home table and we can change this to measures. We can also
can change this to measures. We can also do this the same for median yearly
do this the same for median yearly salary. I'm going to change this one to
salary. I'm going to change this one to measures as well. Now inside of here in
measures as well. Now inside of here in our measures table we have our measures.
our measures table we have our measures. Now you will notice it does have this
Now you will notice it does have this column. If I click on this and then go
column. If I click on this and then go into the table view, you have to have a
into the table view, you have to have a column which is blank. You can't get rid
column which is blank. You can't get rid of that. That just has to be there. And
of that. That just has to be there. And just a reminder from last lesson, it
just a reminder from last lesson, it doesn't matter where these measures are
doesn't matter where these measures are as we moved them. The measures, as we
as we moved them. The measures, as we can see here, um we're using this job
can see here, um we're using this job count in the x-axis right here. The
count in the x-axis right here. The measures are still going to work the
measures are still going to work the same. Now, besides keeping them
same. Now, besides keeping them organized in a certain location, the
organized in a certain location, the next thing that is widely done is
next thing that is widely done is commenting to make sure that you're
commenting to make sure that you're documenting what this measure actually
documenting what this measure actually does. What do I mean by this? I'm going
does. What do I mean by this? I'm going to expand this down to full full view so
to expand this down to full full view so that way we can see it. I'm going to
that way we can see it. I'm going to press shift enter so that way we can
press shift enter so that way we can navigate down and we can insert in
navigate down and we can insert in what's called a comment. How I do this
what's called a comment. How I do this is I can do two forward slashes as shown
is I can do two forward slashes as shown here. And everything after this on this
here. And everything after this on this line is not going to get interpreted.
line is not going to get interpreted. And I can put in something like this of
And I can put in something like this of that calculates the median yearly salary
that calculates the median yearly salary across all job postings. If I wanted to
across all job postings. If I wanted to put another line down, I press shift
put another line down, I press shift enter, put in two forward slashes, and
enter, put in two forward slashes, and then I could put in something like this
then I could put in something like this of uses median over average to account
of uses median over average to account for high salary outliers. Also,
for high salary outliers. Also, typically what we're going to see is
typically what we're going to see is that the name of the measure is on the
that the name of the measure is on the first line and then pressing shift enter
first line and then pressing shift enter after median. The function or the next
after median. The function or the next function begins on the next line. And
function begins on the next line. And from time to time, you may see me, this
from time to time, you may see me, this one only has one variable, so this is
one only has one variable, so this is actually fine. But from time to time,
actually fine. But from time to time, you may see me putting variables on
you may see me putting variables on their own separate line and then having
their own separate line and then having it in this manner. Regardless, even if I
it in this manner. Regardless, even if I press enter right here, close out of
press enter right here, close out of this formula bar, everything underneath
this formula bar, everything underneath this is working just fine. That is using
this is working just fine. That is using this measure. So, I can verify this is
this measure. So, I can verify this is using that median yearly salary measure.
using that median yearly salary measure. Now, let's clean up this job count as
Now, let's clean up this job count as well. I'm going to bring this one on
well. I'm going to bring this one on down here. And then we're going to
down here. And then we're going to insert in a multi-line comma. There's
insert in a multi-line comma. There's going to be multiple lines in here. And
going to be multiple lines in here. And how we can do this is we do a forward
how we can do this is we do a forward slash asterisk. And then I'm going to
slash asterisk. And then I'm going to shift enter, shift enter, shift enter.
shift enter, shift enter, shift enter. And then we can close off this comment
And then we can close off this comment by doing an asterisk and then forward
by doing an asterisk and then forward slash. Now, anything we put inside of
slash. Now, anything we put inside of here is going to be commented off. And
here is going to be commented off. And we can see that it's all commented by
we can see that it's all commented by this new text that I just stuck in here
this new text that I just stuck in here as it's all green. The syntax
as it's all green. The syntax highlighting is pretty helpful. And I
highlighting is pretty helpful. And I just put that it calculates the total
just put that it calculates the total count of jobs and it's used as a
count of jobs and it's used as a denominator as we're going to show in
denominator as we're going to show in various per job calculations. Now I want
various per job calculations. Now I want to switch this actually and we're going
to switch this actually and we're going to be using now instead count rows and
to be using now instead count rows and we're using count rows because every row
we're using count rows because every row in this table of job postings fact is a
in this table of job postings fact is a single job posting or the count of a
single job posting or the count of a job. So we're going to do that. Anyway,
job. So we're going to do that. Anyway, I just want to show before this. This is
I just want to show before this. This is what's really neat about measures and
what's really neat about measures and what I really love about them. Right? So
what I really love about them. Right? So we have this used inside of here. These
we have this used inside of here. These top two tables here that are using that
top two tables here that are using that job count. If for some reason I need to
job count. If for some reason I need to update a measure, all I have to do is
update a measure, all I have to do is just come in here, insert in the new
just come in here, insert in the new formula that I want to use for this. I
formula that I want to use for this. I want to use count rows. In this case,
want to use count rows. In this case, for count rows, it counts the number of
for count rows, it counts the number of rows in a table. So I only need to list
rows in a table. So I only need to list a table of job postings fact. Close the
a table of job postings fact. Close the parenthesis. Press enter. And then
parenthesis. Press enter. And then navigating back in here, these values
navigating back in here, these values didn't change because both of them were
didn't change because both of them were basically calculating the same thing. I
basically calculating the same thing. I just prefer count uh rows over this. But
just prefer count uh rows over this. But all of the different reports and
all of the different reports and canvases that I'm using to use this
canvases that I'm using to use this measure are updated as well. Measures
measure are updated as well. Measures are great because they allow us to have
are great because they allow us to have a single source of truth. So you can
a single source of truth. So you can catch yourself from inadvertently doing
catch yourself from inadvertently doing wrong calculations with implicit
wrong calculations with implicit measures. Explicit measures help prevent
measures. Explicit measures help prevent that.
So we've been doing previously a lot of job count and median yearly salary.
job count and median yearly salary. Let's actually change this up a little
Let's actually change this up a little bit and let's start putting to use those
bit and let's start putting to use those skills. What we're going to be
skills. What we're going to be calculating are these two measures.
calculating are these two measures. First, the easier one is that we want to
First, the easier one is that we want to calculate the skill count. So, how many
calculate the skill count. So, how many skills are associated for a certain job
skills are associated for a certain job title. Granted, this number doesn't
title. Granted, this number doesn't really help us that much because if
really help us that much because if there's more job postings, the higher
there's more job postings, the higher the job count, the higher the skill
the job count, the higher the skill count. So there's nothing we can do with
count. So there's nothing we can do with this until we turn it into a ratio of
this until we turn it into a ratio of skills per job. And in that case, we can
skills per job. And in that case, we can then see uh what is the amount of skills
then see uh what is the amount of skills per a job actually normalized out. So
per a job actually normalized out. So let's get into building this. I'm going
let's get into building this. I'm going to start a new page for us to visualize
to start a new page for us to visualize this on. And we're going to do our first
this on. And we're going to do our first measure. We want to do it right inside
measure. We want to do it right inside of that measures table. We want to do
of that measures table. We want to do that skill count. So I'm going to
that skill count. So I'm going to rightclick it and select new measure.
rightclick it and select new measure. Now for this we want to calculate
Now for this we want to calculate obviously skill count. Keep the name
obviously skill count. Keep the name real original. Use shift enter to go
real original. Use shift enter to go down to the next line. And we're going
down to the next line. And we're going to follow a similar approach that we did
to follow a similar approach that we did for job count in that we're going to use
for job count in that we're going to use count rows. And we want to use the
count rows. And we want to use the skills job dim. Then we'll go ahead and
skills job dim. Then we'll go ahead and close this function. Now, it's important
close this function. Now, it's important to note we don't want to do the skills
to note we don't want to do the skills dim because remember the skills dim
dim because remember the skills dim table is only a list of a single skill
table is only a list of a single skill in there. We want to look at the skills
in there. We want to look at the skills job dim specifically the skill skill IDs
job dim specifically the skill skill IDs cuz this has the list of each every
cuz this has the list of each every individual skill and we can see it from
individual skill and we can see it from the table view as well. Hey, there's
the table view as well. Hey, there's multiple different jobs that can have
multiple different jobs that can have multiple different skills. Anyway,
multiple different skills. Anyway, navigating back into our report view.
navigating back into our report view. Looks like skill count. Skill count
Looks like skill count. Skill count disappeared. I'm going to go ahead and
disappeared. I'm going to go ahead and select it again because I do want to add
select it again because I do want to add a comment on here. Shift enter down. And
a comment on here. Shift enter down. And I'm just going to put in it's used to
I'm just going to put in it's used to find the total count of skills for a job
find the total count of skills for a job posting. Now, anytime I'm making any of
posting. Now, anytime I'm making any of these skills, I typically like to use
these skills, I typically like to use either a matrix or a table to make sure
either a matrix or a table to make sure that it's calculating correctly as I go.
that it's calculating correctly as I go. Feel is a little bit easier than using
Feel is a little bit easier than using any other charts or visualizations. And
any other charts or visualizations. And for this, we want to look at the job
for this, we want to look at the job title short level. So, I can put that
title short level. So, I can put that into the rows. Putting this into focus
into the rows. Putting this into focus mode so we can actually see it a little
mode so we can actually see it a little better. I can then do things like drag
better. I can then do things like drag the skill count into the values column.
the skill count into the values column. And I'm noticing right now it's not
And I'm noticing right now it's not really formatted how I want it. I can
really formatted how I want it. I can select it. This measure tools come up.
select it. This measure tools come up. I'm going to put in a comma. All right,
I'm going to put in a comma. All right, looking good. Not too bad. I want to get
looking good. Not too bad. I want to get out of this. Anytime I want the formula
out of this. Anytime I want the formula bar to disappear, I can just click over
bar to disappear, I can just click over here in the data pane and select like
here in the data pane and select like another table just to get rid of it.
another table just to get rid of it. Granted, it can't be a calculated table.
Granted, it can't be a calculated table. Anyway, now we want to get skills per
Anyway, now we want to get skills per job. And conveniently, we've already
job. And conveniently, we've already done the job count. So, I'm going to
done the job count. So, I'm going to drag it down here. What we can do is we
drag it down here. What we can do is we can divide the skill count measure by
can divide the skill count measure by the job count measure. So, let's create
the job count measure. So, let's create this measure. I'm going to rightclick
this measure. I'm going to rightclick measure, select new measure. We're going
measure, select new measure. We're going to call this skill per job. And for this
to call this skill per job. And for this one, we could do skill count, which the
one, we could do skill count, which the measure pops up, and then job count
measure pops up, and then job count divided by in this type of syntax. It's
divided by in this type of syntax. It's going to be perfectly fine. I can go
going to be perfectly fine. I can go skills per job, drag it into here. It's
skills per job, drag it into here. It's calculating correctly. This is good, but
calculating correctly. This is good, but not necessarily best practice. Instead,
not necessarily best practice. Instead, what I would like to see is I would use
what I would like to see is I would use the divide function. And it's a safe
the divide function. And it's a safe divide function with the ability to
divide function with the ability to handle divide by zero cases. So you
handle divide by zero cases. So you don't have to deal with errors and stuff
don't have to deal with errors and stuff like that. In there, we just specify the
like that. In there, we just specify the nu numerator of skill count and then
nu numerator of skill count and then also the denominator of job count. Press
also the denominator of job count. Press enter. None of the values change. And
enter. None of the values change. And then as best practice inside of here,
then as best practice inside of here, I'm going to just enter in a comment
I'm going to just enter in a comment that's used to find the ratio of skills
that's used to find the ratio of skills required for job postings. Looks good.
required for job postings. Looks good. One thing is I don't like that it has
One thing is I don't like that it has two decimal places. So I'll select it
two decimal places. So I'll select it and we're just going to put it down to
and we're just going to put it down to one decimal place. It's just tmi. We
one decimal place. It's just tmi. We don't need all that information. All
don't need all that information. All right. Now sorting this table, we can
right. Now sorting this table, we can see that things like senior data
see that things like senior data engineer, data engineers, senior data
engineer, data engineers, senior data scientists, they're requiring more
scientists, they're requiring more skills, whereas data analysts, business
skills, whereas data analysts, business analysts are requiring less skills. This
analysts are requiring less skills. This looks like it honestly correlates to
looks like it honestly correlates to something else that we've calculated
something else that we've calculated previously. If I were to drag the median
previously. If I were to drag the median yearly salary also into here, we can see
yearly salary also into here, we can see that there's a very strange correlation
that there's a very strange correlation going on here. Almost like we could put
going on here. Almost like we could put this into a scatter plot or something.
this into a scatter plot or something. So, I'm going to insert in a scatter
So, I'm going to insert in a scatter plot. Go into focus mode. I'm going to
plot. Go into focus mode. I'm going to drag the median yearly salary into the
drag the median yearly salary into the x-axis. So, nice. It actually has the
x-axis. So, nice. It actually has the right column title and is formatted to
right column title and is formatted to the right currency. And then I'm going
the right currency. And then I'm going to drag skills per job into the yaxis.
to drag skills per job into the yaxis. Now there's only one value. We want to
Now there's only one value. We want to break this up by job titles. Right? So
break this up by job titles. Right? So I'm going to take the job title short
I'm going to take the job title short and drag it into the values portion.
and drag it into the values portion. I'll rename this as job title. And bam.
I'll rename this as job title. And bam. Look at this correlation. I can even go
Look at this correlation. I can even go in and insert in a trend line. Turn it
in and insert in a trend line. Turn it on. This thing is definitely looking
on. This thing is definitely looking like there's some correlation between
like there's some correlation between the number of skills and what is the
the number of skills and what is the median yearly salary. I probably would
median yearly salary. I probably would take this one step further under format
take this one step further under format your visual and I would turn on category
your visual and I would turn on category labels. So now that we can actually see
labels. So now that we can actually see where the different job titles are and
where the different job titles are and actually read it face on.
We're going to shift gears a little bit and get theoretical specifically with
and get theoretical specifically with these measures and with using DAX.
these measures and with using DAX. There's different contexts that can
There's different contexts that can actually happen. We're going to go
actually happen. We're going to go through one by one and see how these
through one by one and see how these different contexts can affect a in our
different contexts can affect a in our case measure or even calculated columns.
case measure or even calculated columns. Overall, it's important to understand
Overall, it's important to understand row context takes less priority than
row context takes less priority than query context and takes less priority
query context and takes less priority than filter context. That's getting an
than filter context. That's getting an error of herself. Let's actually just
error of herself. Let's actually just look at what the heck is row context
look at what the heck is row context first. So, what the heck is row context?
first. So, what the heck is row context? Well, as shown by this visual, row
Well, as shown by this visual, row context refers to in this table the
context refers to in this table the current row that a calculation is being
current row that a calculation is being applied. Specifically, we do we're doing
applied. Specifically, we do we're doing a day of the week calculation and it's
a day of the week calculation and it's looking at only that current row in
looking at only that current row in order to get that final answer of five
order to get that final answer of five for the day of week of January 4th for
for the day of week of January 4th for that Thursday. And we can demonstrate
that Thursday. And we can demonstrate this by creating a new column and for
this by creating a new column and for the day of week setting this equal to
the day of week setting this equal to the function of week day and specifying
the function of week day and specifying job posted date. So these DAX
job posted date. So these DAX calculations inside of this calculated
calculations inside of this calculated column are evaluating on a row context
column are evaluating on a row context label. I say label I mean level.
label. I say label I mean level. Now let's actually take this
Now let's actually take this calculation. We don't need to calculate
calculation. We don't need to calculate day of week in here. I'm not going to
day of week in here. I'm not going to keep this one. Let's actually calculate
keep this one. Let's actually calculate something useful. Specifically, we did
something useful. Specifically, we did this explicit measure of skill per job.
this explicit measure of skill per job. Is there a way we could use row context
Is there a way we could use row context and provide how many skills are
and provide how many skills are associated with a certain job? What we
associated with a certain job? What we would need to do is do a calculated
would need to do is do a calculated column in this job postings fact table
column in this job postings fact table and query the skills job dim table to
and query the skills job dim table to get for every job posting what is the
get for every job posting what is the count of the associated rows for that
count of the associated rows for that particular job posting. So how will we
particular job posting. So how will we do this? Well, I'm going to call this a
do this? Well, I'm going to call this a the skill count and we're going to be
the skill count and we're going to be doing count rows. And then it says, hey,
doing count rows. And then it says, hey, insert a table. So like I said, we're
insert a table. So like I said, we're going to insert in skills job dim and
going to insert in skills job dim and then go ahead and press enter. Now the
then go ahead and press enter. Now the problem is this is as you can see it's
problem is this is as you can see it's 2.2 million which if we remember or we
2.2 million which if we remember or we can just actually navigate to it. We
can just actually navigate to it. We don't have to remember skills job dim is
don't have to remember skills job dim is 2.2 million rows long. So this
2.2 million rows long. So this calculation that's going on inside of
calculation that's going on inside of our fact table it's not right.
our fact table it's not right. Specifically I'm going to get rid of
Specifically I'm going to get rid of that value. We need to use a function
that value. We need to use a function called related table and it returns the
called related table and it returns the related table filtered so that it only
related table filtered so that it only includes the related rows. And then from
includes the related rows. And then from there we can insert in skill job dim.
there we can insert in skill job dim. Put two closing parentheses on here.
Put two closing parentheses on here. Press enter. Wa bing bang. We have an
Press enter. Wa bing bang. We have an answer. This is pretty neat. And it says
answer. This is pretty neat. And it says what skills or how many skills are
what skills or how many skills are associated for each of these different
associated for each of these different jobs. This is once again demonstrating
jobs. This is once again demonstrating that row context analysis.
Now after row context, the next thing that's evaluated is the query context.
that's evaluated is the query context. And this determines which rows from a
And this determines which rows from a table are included in a calculation
table are included in a calculation based on the filtered selection and
based on the filtered selection and visuals, relationships between tables,
visuals, relationships between tables, and then slicers and cross filtering.
and then slicers and cross filtering. So, let's demonstrate query context that
So, let's demonstrate query context that can be used to filter these visuals. We
can be used to filter these visuals. We can do something like drag a slicer into
can do something like drag a slicer into here. And I'm going to drag job tile
here. And I'm going to drag job tile shorten here. Anyway, I can adjust the
shorten here. Anyway, I can adjust the query context by changing which values
query context by changing which values we want to see. So, we can see business
we want to see. So, we can see business analyst or data analyst. And this query
analyst or data analyst. And this query context will filter us down to in our
context will filter us down to in our case, we select the data analyst. It
case, we select the data analyst. It modifies the what this visual is going
modifies the what this visual is going to show. Other ways we could do this of
to show. Other ways we could do this of adjusting the query context is actually
adjusting the query context is actually going into the filters and selecting
going into the filters and selecting what we want it to show here on the
what we want it to show here on the page. This applies this query context
page. This applies this query context plays the filters on this visual filters
plays the filters on this visual filters on this page and filters on all pages.
on this page and filters on all pages. And the other thing that query context
And the other thing that query context is controlled by is cross filtering. So
is controlled by is cross filtering. So if I select something like a machine
if I select something like a machine learning engineer, it will cross filter
learning engineer, it will cross filter there. This has applies a query context
there. This has applies a query context of machine learning engineer. Query
of machine learning engineer. Query context in my opinion is a little bit
context in my opinion is a little bit more abstract in that this is the
more abstract in that this is the specification sent by the visual itself
specification sent by the visual itself whether doing that cross filtering
whether doing that cross filtering filtering or even using slicers.
The last one to discuss is filter context and filter context is applied on
context and filter context is applied on top of query context and on top of row
top of query context and on top of row context. We're going to demonstrate this
context. We're going to demonstrate this shortly in that we can explicitly modify
shortly in that we can explicitly modify using DAX functions like calculate in
using DAX functions like calculate in order to control this filter context and
order to control this filter context and thus undo things that are within the
thus undo things that are within the query or even row context. That's why
query or even row context. That's why we're just covering this cuz you need to
we're just covering this cuz you need to understand there's different contexts.
understand there's different contexts. So let's demonstrate this filter
So let's demonstrate this filter context. And for this we're going to be
context. And for this we're going to be using our skill count column that we
using our skill count column that we just created. Remember, skill count is
just created. Remember, skill count is calculated at the row context level
calculated at the row context level because it's a calculated column. And
because it's a calculated column. And what we're going to be building with is
what we're going to be building with is this visualization here where we can get
this visualization here where we can get a sum of that skill count calculated
a sum of that skill count calculated column based on a different job title.
column based on a different job title. But we can modify the filter context. If
But we can modify the filter context. If you notice here, we get 2.2 million
you notice here, we get 2.2 million grand total skill count. It's basically
grand total skill count. It's basically undoing that query context and modifying
undoing that query context and modifying that filter context. Anyway, let's jump
that filter context. Anyway, let's jump into it. Anyway, inside of here, I'm
into it. Anyway, inside of here, I'm going to insert another matrix down at
going to insert another matrix down at the bottom. Remember, we want to do this
the bottom. Remember, we want to do this by the job title short on the rows. And
by the job title short on the rows. And previously, right, we created that skill
previously, right, we created that skill count calculated column. And I'm going
count calculated column. And I'm going to drag that into the values. I'm going
to drag that into the values. I'm going to put this into focus mode so we can
to put this into focus mode so we can see it. I'm not liking how this
see it. I'm not liking how this formatted, so I'm going to select skill
formatted, so I'm going to select skill count. We're going to change this to put
count. We're going to change this to put a comma there. We're also going to sort
a comma there. We're also going to sort this from high to low. Okay, so this is
this from high to low. Okay, so this is showing us the counts of the skills
showing us the counts of the skills based on the different job title. We can
based on the different job title. We can also confirm this. I'm going to remove
also confirm this. I'm going to remove this, but I can drag in skill count from
this, but I can drag in skill count from our measures and they are again the same
our measures and they are again the same values. So we are confirming that our
values. So we are confirming that our calculated column is correct. Anyway,
calculated column is correct. Anyway, let's say we want a column that has the
let's say we want a column that has the total counts of skills in there. For
total counts of skills in there. For this one, we're going to create a new
this one, we're going to create a new measure and we call this grand total
measure and we call this grand total skill count. And I'm going shift enter
skill count. And I'm going shift enter down. And so normally we would do
down. And so normally we would do something like this. We would do sum of.
something like this. We would do sum of. Remember we created that calculated
Remember we created that calculated column skill count. So I can go ahead
column skill count. So I can go ahead and insert that in here. Close it. Press
and insert that in here. Close it. Press enter. I'm going to just drag it in.
enter. I'm going to just drag it in. This is not what we want just yet. We
This is not what we want just yet. We still have to do modified. I'm going to
still have to do modified. I'm going to drag it into the values. But it's doing
drag it into the values. But it's doing that calculation here. I'm not liking
that calculation here. I'm not liking how it's formatted. I'm going to format
how it's formatted. I'm going to format it correctly real quick. Anyway, that's
it correctly real quick. Anyway, that's not what we want, right? We want to get
not what we want, right? We want to get it to this where we actually see the
it to this where we actually see the grand total skill count popping up.
grand total skill count popping up. Basically modifying that filter context.
Basically modifying that filter context. Well, for this we're going to use a very
Well, for this we're going to use a very popular function that you need to get
popular function that you need to get down and that is called calculate. This
down and that is called calculate. This evaluates an expression within a
evaluates an expression within a modified filtered context. Hence, we can
modified filtered context. Hence, we can modify our filter context. So, this
modify our filter context. So, this allows us to do it. Now, calculate is
allows us to do it. Now, calculate is pretty simple in how we're going to
pretty simple in how we're going to execute it. Let's actually type it out
execute it. Let's actually type it out instead of looking at it here. I don't
instead of looking at it here. I don't like how it's written. I'm going to
like how it's written. I'm going to shift enter down. Type in calculate and
shift enter down. Type in calculate and then open parenthesis. All right. The
then open parenthesis. All right. The first thing is it accepts an expression.
first thing is it accepts an expression. In our case, this formula that we put in
In our case, this formula that we put in right here, this is an expression. I'm
right here, this is an expression. I'm going to tab it over. So that is our
going to tab it over. So that is our expression. And then I'm going to put a
expression. And then I'm going to put a comma. And then we can apply a filter
comma. And then we can apply a filter after that. And that's actually optional
after that. And that's actually optional as noted in the square brackets. So,
as noted in the square brackets. So, what I'm going to do is I'm just going
what I'm going to do is I'm just going to shift enter down and put in another
to shift enter down and put in another parenthesis. Press enter. Anyway, if we
parenthesis. Press enter. Anyway, if we notice after running this, this grand
notice after running this, this grand total skill count did not change. It
total skill count did not change. It still correlates. So, the formula still
still correlates. So, the formula still works the same using calculate. But now
works the same using calculate. But now I want to put on a filter into it.
I want to put on a filter into it. Filters are pretty easy and you probably
Filters are pretty easy and you probably know how to write them yourself. I'm
know how to write them yourself. I'm going to do shift enter. I could do a
going to do shift enter. I could do a filter something like this where I want
filter something like this where I want to filter the job title short to be
to filter the job title short to be equal to data analyst and then running
equal to data analyst and then running this we can see from this that all these
this we can see from this that all these values here are equal to that of the
values here are equal to that of the data analyst so that filter context
data analyst so that filter context overwrites it but we want to get that
overwrites it but we want to get that grand total so we want to look at the
grand total so we want to look at the entire table if you will so we can use
entire table if you will so we can use this function all it's also a popular
this function all it's also a popular function that you should know it returns
function that you should know it returns all rows in a table or values in a
all rows in a table or values in a column, ignoring any filters that may
column, ignoring any filters that may have been applied. So, I'm going to
have been applied. So, I'm going to remove this filter that we just made.
remove this filter that we just made. I'm going to type in that all function,
I'm going to type in that all function, and it takes a table name or column
and it takes a table name or column name. Our calculated column is in that
name. Our calculated column is in that job postings fact table. So, we're going
job postings fact table. So, we're going to go ahead and put this. I'm going to
to go ahead and put this. I'm going to press enter. And bam, now we have that
press enter. And bam, now we have that value overriding and inputting it
value overriding and inputting it through our filter context. So, in
through our filter context. So, in recap, there are three different types
recap, there are three different types of context. filter context which we most
of context. filter context which we most recently covered has the highest
recently covered has the highest precedence. It overrides query and row
precedence. It overrides query and row context and you explicitly modify
context and you explicitly modify calculation environment using functions
calculation environment using functions like calculate like we did. Next up is
like calculate like we did. Next up is query context. It determines what subset
query context. It determines what subset of data to include based on the visual
of data to include based on the visual selection using things like cross filter
selection using things like cross filter filtering or even inside of a matrix how
filtering or even inside of a matrix how it can come out there. query context is
it can come out there. query context is going to override our row context level
going to override our row context level which has the lowest precedence and it
which has the lowest precedence and it operates at that individual row level
operates at that individual row level like we demonstrated with calculated
like we demonstrated with calculated columns. Now this is an advanced topic
columns. Now this is an advanced topic but it's important that you understand
but it's important that you understand what's going on here because you're
what's going on here because you're going to get yourself into trouble if
going to get yourself into trouble if you don't understand this precedence and
you don't understand this precedence and you start building more complex
you start building more complex calculations with DAX. Trust me, I've
calculations with DAX. Trust me, I've gotten myself into plenty of trouble
gotten myself into plenty of trouble with this.
with this. Now, let's put this knowledge of
Now, let's put this knowledge of different contexts to the test by
different contexts to the test by building this visual here, which we're
building this visual here, which we're going to be able to break down basically
going to be able to break down basically what is the median yearly salary for all
what is the median yearly salary for all job postings and what is using modifying
job postings and what is using modifying our filter context, what is the median
our filter context, what is the median yearly salary of only the US and we're
yearly salary of only the US and we're going to be able to evaluate this at a
going to be able to evaluate this at a skill count level. So, let's get into
skill count level. So, let's get into building it. For this, I'm going to
building it. For this, I'm going to remove some room and I'm going to remove
remove some room and I'm going to remove the slicer. So, we've already calculated
the slicer. So, we've already calculated this median yearly salary. I want to now
this median yearly salary. I want to now calculate what is the median year uh
calculate what is the median year uh yearly salary just for the United
yearly salary just for the United States. You can also just modify this to
States. You can also just modify this to any country that you that you live in.
any country that you that you live in. Um so, feel free to do that if you want
Um so, feel free to do that if you want to. Anyway, what I'm going to do to keep
to. Anyway, what I'm going to do to keep things simple, I'm just going to copy
things simple, I'm just going to copy all this here and inside of measures,
all this here and inside of measures, I'm going to create a new measure. I'm
I'm going to create a new measure. I'm going to paste it in. We want to do this
going to paste it in. We want to do this for the US. So this is my new measure
for the US. So this is my new measure and I'll modify the comment so that way
and I'll modify the comment so that way it says for the United States. Now
it says for the United States. Now remember in order to do this we going we
remember in order to do this we going we are going to use the calculate function.
are going to use the calculate function. So I'm going to type in calculate and
So I'm going to type in calculate and then shift enter down. We want to do the
then shift enter down. We want to do the median value of salary year average and
median value of salary year average and we want to put a filter on it. So I'm
we want to put a filter on it. So I'm going shift enter down for that. And for
going shift enter down for that. And for that filter, we want to make sure that
that filter, we want to make sure that the job country is equal to the United
the job country is equal to the United States. If you do a different country,
States. If you do a different country, you need to make sure that you spell it
you need to make sure that you spell it correctly. Okay, I'm going to go ahead
correctly. Okay, I'm going to go ahead and press shift enter and then close the
and press shift enter and then close the parenthesis and press enter. So, let's
parenthesis and press enter. So, let's actually see this bad boy in action. I'm
actually see this bad boy in action. I'm going to create a clustered bar chart
going to create a clustered bar chart down here. And I'm going drag the median
down here. And I'm going drag the median yearly salary into the x- axis and
yearly salary into the x- axis and median yearly salary for the US also in
median yearly salary for the US also in here. Making it slightly bigger. We can
here. Making it slightly bigger. We can see which is pretty interesting. The
see which is pretty interesting. The median salary for the US is slightly
median salary for the US is slightly lower. Also not liking how this number's
lower. Also not liking how this number's formatted. I'm going select this format
formatted. I'm going select this format as currency and change this to zero
as currency and change this to zero decimal places. Now, one thing to note
decimal places. Now, one thing to note with this calculation that we currently
with this calculation that we currently have, median yearly salary, I retyped in
have, median yearly salary, I retyped in this right here, which if we look at the
this right here, which if we look at the median yearly salary, it is the same
median yearly salary, it is the same calculation. And it looks like it does
calculation. And it looks like it does hint uh this red highlighting mainly
hint uh this red highlighting mainly because normally it's not written like
because normally it's not written like this with this extra spacing. I just did
this with this extra spacing. I just did that for demo purposes earlier. So, I'm
that for demo purposes earlier. So, I'm going to clean that up real quick. Press
going to clean that up real quick. Press enter. Anyway, this is the same thing.
enter. Anyway, this is the same thing. So inside of this median yearly salary
So inside of this median yearly salary what would actually be better practice
what would actually be better practice instead of using this is referencing
instead of using this is referencing directly that other measure itself it is
directly that other measure itself it is still an expression whenever I press
still an expression whenever I press enter the value is still the same um so
enter the value is still the same um so I know it's working and yeah and so this
I know it's working and yeah and so this case we're still using that filter
case we're still using that filter context to filter down to this now we
context to filter down to this now we want to get it by the count of skills so
want to get it by the count of skills so in that job postings t fact table I'm
in that job postings t fact table I'm going to drag in the skill count to the
going to drag in the skill count to the y-axis. Now, it goes all the way up to
y-axis. Now, it goes all the way up to this level, which looks like it's like
this level, which looks like it's like 35. But when we get start getting
35. But when we get start getting higher, right, there's less values
higher, right, there's less values because the likelihood that there's 34
because the likelihood that there's 34 skills in a job posting is pretty low.
skills in a job posting is pretty low. So, I'm going to filter it down. So,
So, I'm going to filter it down. So, we'll adjust the query context by going
we'll adjust the query context by going to filters. Know it's sort of
to filters. Know it's sort of counterintuitive, but we're adjusting
counterintuitive, but we're adjusting the query context in this case. We'll
the query context in this case. We'll leave it as advanced filter, and we'll
leave it as advanced filter, and we'll say when it's less than, we'll say 15
say when it's less than, we'll say 15 values. All right, so not bad. We can
values. All right, so not bad. We can clearly see with this that for less
clearly see with this that for less skills, you get paid less money. And as
skills, you get paid less money. And as the skills go up, the pay goes up. And
the skills go up, the pay goes up. And when comparing it to the United States
when comparing it to the United States in our case, honestly, we're not seeing
in our case, honestly, we're not seeing that big of a difference. And that's
that big of a difference. And that's mainly because the United States is such
mainly because the United States is such a large portion of this data set. Feel
a large portion of this data set. Feel free to try out different countries as
free to try out different countries as well, and let me know if you find any
well, and let me know if you find any characteristics about it in the
characteristics about it in the comments.
Now, one quick refresher that we covered all the way back in the first chapter,
all the way back in the first chapter, and that's on DAX query view. You can
and that's on DAX query view. You can also use this to evaluate your different
also use this to evaluate your different measures that you've come up with and
measures that you've come up with and are creating. I just find it's a little
are creating. I just find it's a little bit more difficult as it takes some more
bit more difficult as it takes some more DAX knowledge, but you could actually do
DAX knowledge, but you could actually do this without DAX. In the case of job
this without DAX. In the case of job count, I can rightclick this and they
count, I can rightclick this and they have this quick queries. If I do
have this quick queries. If I do evaluate in the upper portion right
evaluate in the upper portion right here, it writes out the DAX in order to
here, it writes out the DAX in order to get job count below this. So just put it
get job count below this. So just put it anyway, the values down here for job
anyway, the values down here for job count. Now another option is I can
count. Now another option is I can rightclick job count, go to quick
rightclick job count, go to quick queries, I can go to define and evaluate
queries, I can go to define and evaluate making a little bit bigger room with
making a little bit bigger room with this. Now with this one, because I did
this. Now with this one, because I did define and evaluate, it still has the
define and evaluate, it still has the same syntax you notice below. But what
same syntax you notice below. But what is nice about this is they have this
is nice about this is they have this option up here of update update model
option up here of update update model overwrite measures. You can if you want
overwrite measures. You can if you want if you wanted to create or update this
if you wanted to create or update this measure like I could make this back into
measure like I could make this back into using count of job ID and then I can run
using count of job ID and then I can run it. Okay, I'm getting the same value and
it. Okay, I'm getting the same value and then I can just update the model and it
then I can just update the model and it says hey do you want to update the
says hey do you want to update the model? Are you sure? and it updates the
model? Are you sure? and it updates the model that disappears. And whenever I go
model that disappears. And whenever I go into job count when looking at it from
into job count when looking at it from something like the query view, I can see
something like the query view, I can see that okay, it did update. But I don't
that okay, it did update. But I don't actually want to update it. I'm going to
actually want to update it. I'm going to change this back to this bad boy. I'm
change this back to this bad boy. I'm going to say update model and update it.
going to say update model and update it. Here this is a really good environment
Here this is a really good environment in the case like our median yearly
in the case like our median yearly salary. Going to define and evaluate. In
salary. Going to define and evaluate. In our case, right, we had multiple
our case, right, we had multiple different levels of the formula itself.
different levels of the formula itself. This is a good case if you were getting
This is a good case if you were getting complex queries to go in and actually
complex queries to go in and actually edit it and then update the values based
edit it and then update the values based on what you need to mainly just want to
on what you need to mainly just want to share as an option because this DAX
share as an option because this DAX query view is a newer feature inside of
query view is a newer feature inside of PowerBI so some people aren't familiar
PowerBI so some people aren't familiar with it. All right, it's now your turn
with it. All right, it's now your turn to give it a try and jump in creating
to give it a try and jump in creating some different explicit measures and
some different explicit measures and messing around with those different
messing around with those different context to better understand it. With
context to better understand it. With that, there's only one more lesson left
that, there's only one more lesson left and for that we're going to be jumping
and for that we're going to be jumping into parameters and that uses DAX. With
into parameters and that uses DAX. With that, I'll see you there.
Welcome to this last lesson in DAX. And this one, pretty fun one. We're going to
this one, pretty fun one. We're going to be doing it on parameters, which these
be doing it on parameters, which these allow our end users who may not be as
allow our end users who may not be as familiar with all the intricacies of
familiar with all the intricacies of PowerBI to actually change up what
PowerBI to actually change up what inputs they have inside of a chart and
inputs they have inside of a chart and get more of what they want and explore
get more of what they want and explore the data better. Let me show you what I
the data better. Let me show you what I mean. Here I have two charts. The one on
mean. Here I have two charts. The one on the left is showing based on the job
the left is showing based on the job title the median yearly salary. The one
title the median yearly salary. The one right is showing basically the same
right is showing basically the same thing for job count. Anyway, parameters
thing for job count. Anyway, parameters are what we're going to be creating in
are what we're going to be creating in this. And this slicer up in the top
this. And this slicer up in the top allow us to select different parameters.
allow us to select different parameters. So in this case, I can change the yaxis
So in this case, I can change the yaxis from something like the job title to
from something like the job title to skill to even country or even company
skill to even country or even company allowing me to change up this view. And
allowing me to change up this view. And it's not only limited to like in this
it's not only limited to like in this case the y-axis, we could change up the
case the y-axis, we could change up the x-axis. So right now I have selected job
x-axis. So right now I have selected job count for this uh visual below. I could
count for this uh visual below. I could change it to something like median
change it to something like median yearly salary. Now, both of these
yearly salary. Now, both of these examples are what is known as a field
examples are what is known as a field parameter. Now, both of these are known
parameter. Now, both of these are known as a field parameter as we're allowed to
as a field parameter as we're allowed to input into this different column names
input into this different column names or even different measures. Now, besides
or even different measures. Now, besides those, they also have numeric
those, they also have numeric parameters, and this allows us to
parameters, and this allows us to perform more of a whatif analysis.
perform more of a whatif analysis. Here's a scenario we're going to be
Here's a scenario we're going to be doing at the second half of this lesson.
doing at the second half of this lesson. And in it, we're trying to find out,
And in it, we're trying to find out, yeah, what are the top paying jobs, but
yeah, what are the top paying jobs, but more specifically, what is our take-home
more specifically, what is our take-home pay going to be? In the United States,
pay going to be? In the United States, tax rates can be up to 35%.
tax rates can be up to 35%. And this will allow us via a slider to
And this will allow us via a slider to adjust what our different rates are for
adjust what our different rates are for this. And as you can see, it adjusts our
this. And as you can see, it adjusts our final values in the visuals below. Now,
final values in the visuals below. Now, numeric parameters are more prevalent
numeric parameters are more prevalent within forecasting scenarios and even
within forecasting scenarios and even things like financial modeling. So,
things like financial modeling. So, personally, I find this that it comes
personally, I find this that it comes second to those field parameters. So,
second to those field parameters. So, that's why we're covering this second.
Let's jump into creating our first field parameter. And in this one, I want to be
parameter. And in this one, I want to be able to view based on the median yearly
able to view based on the median yearly salary it from different types of views,
salary it from different types of views, if you will. such as job tiles, country,
if you will. such as job tiles, country, company, and also skills. So, we're
company, and also skills. So, we're going to create a parameter to do this.
going to create a parameter to do this. For this, feel free to continue to work
For this, feel free to continue to work with the report from the last lesson, or
with the report from the last lesson, or if you lost, you can just use that
if you lost, you can just use that explicit measures, and we're going to be
explicit measures, and we're going to be taking it off from there. Inside of
taking it off from there. Inside of here, I'm going to create a new page,
here, I'm going to create a new page, and I'm going to name it parameters. So,
and I'm going to name it parameters. So, parameters are accessed underneath the
parameters are accessed underneath the modeling tab. And inside of here under
modeling tab. And inside of here under new parameters, we can make either a
new parameters, we can make either a numeric range or a field parameter. Now,
numeric range or a field parameter. Now, I do want to call out something real
I do want to call out something real quick cuz you've probably seen it
quick cuz you've probably seen it before. And that's with on the home tab
before. And that's with on the home tab under transform data. Transform data. We
under transform data. Transform data. We have a section. Right now, it's grayed
have a section. Right now, it's grayed out, but we have a section called edit
out, but we have a section called edit parameters and also edit variables.
parameters and also edit variables. These, although somewhat related, aren't
These, although somewhat related, aren't the same parameters that we're going to
the same parameters that we're going to create inside of here. Specifically,
create inside of here. Specifically, this is the parameters within Power
this is the parameters within Power Query, hence why it's in that same drop
Query, hence why it's in that same drop down for transform data, which opens up
down for transform data, which opens up the Power Query editor. And these
the Power Query editor. And these parameters are similar in that you can
parameters are similar in that you can use it to change up different fields,
use it to change up different fields, but usually use them to like change to
but usually use them to like change to different data sources very easily.
different data sources very easily. Anyway, that's beyond the scope of this.
Anyway, that's beyond the scope of this. I just wanted to point it out in case
I just wanted to point it out in case you had questions about it. So, back to
you had questions about it. So, back to the modeling tab under new parameters.
the modeling tab under new parameters. We're going to do the first one first of
We're going to do the first one first of fields. If you accidentally select the
fields. If you accidentally select the wrong one, you can change it inside of
wrong one, you can change it inside of here. Anyway, we're changing back to
here. Anyway, we're changing back to fields. And for the name of this, I know
fields. And for the name of this, I know I'm going to put into a slicer. So, I
I'm going to put into a slicer. So, I give it a name that basically cues the
give it a name that basically cues the user in that they can select with this.
user in that they can select with this. So, we can do something like either
So, we can do something like either select category or select value. We'll
select category or select value. We'll just do select category. Next up, we
just do select category. Next up, we need to start dragging the applicable
need to start dragging the applicable columns that we want into there. I know
columns that we want into there. I know I want job title short job country
I want job title short job country skills specifically from the skills
skills specifically from the skills dimensional table because we want that
dimensional table because we want that name and then finally we want company
name and then finally we want company which you actually have to input in name
which you actually have to input in name if you want to get that from company
if you want to get that from company dim. It asks at the bottom do I want to
dim. It asks at the bottom do I want to add the slice to the page? You bet I do.
add the slice to the page? You bet I do. Select create. I'm going to move this
Select create. I'm going to move this slicer down just to show but we have our
slicer down just to show but we have our name of select category and then look at
name of select category and then look at all these names. Especially this one of
all these names. Especially this one of name that's not really readable like
name that's not really readable like what is that? So luckily for us we know
what is that? So luckily for us we know DAX now and this is the formula behind
DAX now and this is the formula behind how this parameter is created. Also with
how this parameter is created. Also with that over here in the right hand side of
that over here in the right hand side of the data pane we have this select
the data pane we have this select category and if we view it within the
category and if we view it within the table view we can see that it has three
table view we can see that it has three different attributes about it or three
different attributes about it or three different columns. It has the select
different columns. It has the select category column, the select category
category column, the select category fields, which it tells it what are those
fields, which it tells it what are those different columns that I should be
different columns that I should be using, and the select category order.
using, and the select category order. What order should it put it specifically
What order should it put it specifically in a slicer? Obviously, you know, we
in a slicer? Obviously, you know, we can't edit it from right here. So, we're
can't edit it from right here. So, we're going to edit it from that formula bar.
going to edit it from that formula bar. Change job title short to just job
Change job title short to just job title, job country to country, skills to
title, job country to country, skills to just skills with a capital S, and then
just skills with a capital S, and then name to company. Pressing enter, see our
name to company. Pressing enter, see our slicer updates below. If I want to
slicer updates below. If I want to change the uh the order in this slicer,
change the uh the order in this slicer, say I wanted skills actually second,
say I wanted skills actually second, which we need to put it number one for
which we need to put it number one for this one and then country uh third. So
this one and then country uh third. So that one needs to be two. Got to love
that one needs to be two. Got to love the index of zero. I can do that and
the index of zero. I can do that and then it updates below as well. All
then it updates below as well. All right, so let's now use this in a
right, so let's now use this in a visualization. I'm going to put select
visualization. I'm going to put select category up in the top and then put a
category up in the top and then put a bar chart underneath it. We want to look
bar chart underneath it. We want to look at the median yearly salary. So, I'll
at the median yearly salary. So, I'll take that and drag that into the x-axis.
take that and drag that into the x-axis. And then normally remember we go for
And then normally remember we go for like the job postings fact table. Drag
like the job postings fact table. Drag in job title shortened to here. But that
in job title shortened to here. But that doesn't help us here, right? Because we
doesn't help us here, right? Because we want to be able to control the actual
want to be able to control the actual view within here. So, we have to add
view within here. So, we have to add this to this visualization. So, I'm
this to this visualization. So, I'm going uncheck this and we want to go to
going uncheck this and we want to go to that select category here. Specifically,
that select category here. Specifically, this of select category, put it into the
this of select category, put it into the yaxis and bam, here it is below. And now
yaxis and bam, here it is below. And now whenever I select different options. So
whenever I select different options. So skills it updates for the skills the
skills it updates for the skills the country and then also company. Now you
country and then also company. Now you can't do multiple values with this. So
can't do multiple values with this. So we need to change this visual to make
we need to change this visual to make sure that it our users work with this
sure that it our users work with this properly. So under format visual I'm
properly. So under format visual I'm going to go into our slicer settings and
going to go into our slicer settings and I'm going to change this to a title
I'm going to change this to a title along with under selection going to make
along with under selection going to make sure that only single select is allowed.
sure that only single select is allowed. Now, we've only demonstrated the y-axis
Now, we've only demonstrated the y-axis in this or the categories. What if we
in this or the categories. What if we want to change this one down here with
want to change this one down here with specifically with different measures we
specifically with different measures we have built? Well, let's create a
have built? Well, let's create a parameter for that. And for this, we're
parameter for that. And for this, we're going to be switching between median
going to be switching between median yearly salary and the total job count.
yearly salary and the total job count. So, under modeling, new parameters,
So, under modeling, new parameters, we'll go to fields. For the name, we'll
we'll go to fields. For the name, we'll use select measure. And inside of here,
use select measure. And inside of here, we're going to drag in that job count
we're going to drag in that job count and then also that median yearly salary
and then also that median yearly salary and click create. These names are
and click create. These names are already good enough for how I like it.
already good enough for how I like it. This is looking good. I do want to
This is looking good. I do want to format this visual in the fact that I
format this visual in the fact that I only want it to be a single select. And
only want it to be a single select. And then also let's make it look similar
then also let's make it look similar being a tile. So now we can switch
being a tile. So now we can switch between this median yearly salary and
between this median yearly salary and this job count. But it's not doing
this job count. But it's not doing anything on our visual. I can create
anything on our visual. I can create another visual. But I actually want to
another visual. But I actually want to demonstrate how we can use this on this
demonstrate how we can use this on this visual right here. So I'm going to
visual right here. So I'm going to remove median yearly salary. And then
remove median yearly salary. And then for select measure, I'm going to drag it
for select measure, I'm going to drag it into the x-axis. I'm going to make this
into the x-axis. I'm going to make this a little bit bigger now. But now I can
a little bit bigger now. But now I can switch up between median yearly salary
switch up between median yearly salary and job count. And we can do this for
and job count. And we can do this for country, company, median, yearly salary.
country, company, median, yearly salary. This is pretty neat and allows a dynamic
This is pretty neat and allows a dynamic access and manipulation of our
access and manipulation of our visualizations. Now, one quick note.
visualizations. Now, one quick note. This one here of select measures.
This one here of select measures. Remember, we're doing the aggregation
Remember, we're doing the aggregation with a measure, but I'm going to demo
with a measure, but I'm going to demo something real quick. You don't have to
something real quick. You don't have to follow along with this portion. I'm
follow along with this portion. I'm going to demo something that doesn't
going to demo something that doesn't work that you need to be aware of when
work that you need to be aware of when building this. Specifically, let's say
building this. Specifically, let's say we're creating a new parameter. We'll
we're creating a new parameter. We'll say it's a field as well, right? And we
say it's a field as well, right? And we wanted to select between yearly and
wanted to select between yearly and hourly salary. Should be yearly or
hourly salary. Should be yearly or hourly salary. Anyway, inside our job
hourly salary. Anyway, inside our job postings fact table, right, we do have
postings fact table, right, we do have this salary hour average and that salary
this salary hour average and that salary year average. I'm going to go ahead and
year average. I'm going to go ahead and just create this. Now, let's say with
just create this. Now, let's say with this slicer, let's say we were just
this slicer, let's say we were just replacing this one up here, and we want
replacing this one up here, and we want to put it inside of this visualization.
to put it inside of this visualization. So, I come to select salary yearly or
So, I come to select salary yearly or hourly, remove the select measures, and
hourly, remove the select measures, and I drag this into the x-axis. Okay, this
I drag this into the x-axis. Okay, this is not going to work. And even when I
is not going to work. And even when I select these different ones, it's not
select these different ones, it's not going to work. And this is because right
going to work. And this is because right these are columns and we're trying to do
these are columns and we're trying to do an aggregation on the xaxis. Previously,
an aggregation on the xaxis. Previously, we were doing either count of jobs or a
we were doing either count of jobs or a median of the salaries. It doesn't know
median of the salaries. It doesn't know what to do by default and so it's not
what to do by default and so it's not even going to make a visual and it's
even going to make a visual and it's going to end up breaking. So going to
going to end up breaking. So going to get rid of this and drag select measures
get rid of this and drag select measures back in like we liked. Additionally, I'm
back in like we liked. Additionally, I'm not keeping this cuz it's broken. So I'm
not keeping this cuz it's broken. So I'm going to remove it. And also I'm going
going to remove it. And also I'm going to delete this from our model because it
to delete this from our model because it doesn't work. All right, so bam back to
doesn't work. All right, so bam back to working properly.
Next up, let's get into a numeric parameter. And for this, we're going to
parameter. And for this, we're going to be building this one here on selecting
be building this one here on selecting the deduction rate. Now, this one we're
the deduction rate. Now, this one we're going to have to do a little bit more
going to have to do a little bit more works because yes, we can set up our
works because yes, we can set up our numeric parameter very similar to how we
numeric parameter very similar to how we set up our field parameter, but then we
set up our field parameter, but then we actually have to implement it into a DAX
actually have to implement it into a DAX calculation or an explicit measure in
calculation or an explicit measure in order to calculate what we're trying to
order to calculate what we're trying to do with this deduction rate. Basically,
do with this deduction rate. Basically, we're trying to take a deduction of the
we're trying to take a deduction of the median yearly salary. So, this one's
median yearly salary. So, this one's going to take multiple steps. So, I
going to take multiple steps. So, I created a new page and then under new
created a new page and then under new parameters, we're going to create that
parameters, we're going to create that numeric range. We'll call this select
numeric range. We'll call this select deduction rate. For the minimum, we're
deduction rate. For the minimum, we're going to be doing zero. Maximum, we'll
going to be doing zero. Maximum, we'll go to we'll say 50%, but in this case,
go to we'll say 50%, but in this case, we need to put a decimal. So 0.5. And
we need to put a decimal. So 0.5. And then for the increments, we're going to
then for the increments, we're going to do that of 0.01
do that of 0.01 increments. For this, the typical tax
increments. For this, the typical tax rate, at least in the United States, is
rate, at least in the United States, is 20%, so we'll do 0.2 for this. So me,
20%, so we'll do 0.2 for this. So me, I'm noticing the red values. I skipped
I'm noticing the red values. I skipped over this. The data type, we have to
over this. The data type, we have to make sure that this is a decimal number.
make sure that this is a decimal number. Anyway, all those red boxes are cleared.
Anyway, all those red boxes are cleared. We want to add a slicer to this page.
We want to add a slicer to this page. Create. Okay. I'm going to drag that
Create. Okay. I'm going to drag that across the top here. Next up, let's
across the top here. Next up, let's create a visualization that we can
create a visualization that we can actually use this on. So, I'm going to
actually use this on. So, I'm going to insert in a stack bar chart and we'll
insert in a stack bar chart and we'll have median yearly salary on the x-axis
have median yearly salary on the x-axis and then a job title short on the yaxis.
and then a job title short on the yaxis. I'm going to change this name to job
I'm going to change this name to job title. Now we need to go into
title. Now we need to go into implementing this into where we want to
implementing this into where we want to take whatever deduction rate we select
take whatever deduction rate we select from here from our slicer to basically
from here from our slicer to basically deduct from our median yearly salary
deduct from our median yearly salary here. One quick note, notice I made an
here. One quick note, notice I made an error. I have the stack bar chart. We
error. I have the stack bar chart. We want these the new measure that we
want these the new measure that we created right next to it. So I'm going
created right next to it. So I'm going to change this to a clustered bar chart.
to change this to a clustered bar chart. Should be no change visually. So let's
Should be no change visually. So let's get into creating this measure using
get into creating this measure using median yearly salary. So I'm going to
median yearly salary. So I'm going to say I want a new measure. We'll call
say I want a new measure. We'll call this median yearly take-home pay. Press
this median yearly take-home pay. Press shift enter to get down. And for this,
shift enter to get down. And for this, we want to use that median yearly salary
we want to use that median yearly salary value. And then we want to subtract our
value. And then we want to subtract our deduction rate. So, we're going to do a
deduction rate. So, we're going to do a little bit of algebra here. We're going
little bit of algebra here. We're going to multiply times 1 minus that deduction
to multiply times 1 minus that deduction rate. But what the heck is that? How how
rate. But what the heck is that? How how do we get this deduction rate in here?
do we get this deduction rate in here? Well, if we go to that select deduction
Well, if we go to that select deduction rate right here, and it's giving me an
rate right here, and it's giving me an error right now because I exited out of
error right now because I exited out of that. It's fine. I have notice compared
that. It's fine. I have notice compared to the other ones of select category,
to the other ones of select category, they only have one value, but select
they only have one value, but select deduction rate has two values. And this
deduction rate has two values. And this second one right here is, we can see by
second one right here is, we can see by the icon, a measure, and that's what we
the icon, a measure, and that's what we want to use. We want to use that select
want to use. We want to use that select deduction rate. So, typing in select
deduction rate. So, typing in select deduction rate, it's popping right up.
deduction rate, it's popping right up. I'm going to do that and then close the
I'm going to do that and then close the parentheses. So, just so you're aware of
parentheses. So, just so you're aware of what's going on here, right? If I have a
what's going on here, right? If I have a deduction rate of 20 or 0.2, we're going
deduction rate of 20 or 0.2, we're going to do 1 minus.2 that gives8.8
to do 1 minus.2 that gives8.8 times our median yearly salary. Makes
times our median yearly salary. Makes sense. Let's press enter. Now, whenever
sense. Let's press enter. Now, whenever we do this and move this, nothing's
we do this and move this, nothing's going to happen because we haven't added
going to happen because we haven't added to our chart. So, with our visual
to our chart. So, with our visual selected, I'm going add median yearly
selected, I'm going add median yearly take-home pay underneath here. And now
take-home pay underneath here. And now whenever we adjust this we can see what
whenever we adjust this we can see what it needs to be. So at 0% just testing it
it needs to be. So at 0% just testing it out both of these are equal as expected
out both of these are equal as expected and then doing a 50% it is half of this.
and then doing a 50% it is half of this. So pretty neat implementation of numeric
So pretty neat implementation of numeric parameters.
Now DAX has a lot more features to cover more than I can cover in this video.
more than I can cover in this video. Frankly, I can make a whole course about
Frankly, I can make a whole course about it and I did actually twice on data camp
it and I did actually twice on data camp specifically. I have two other courses I
specifically. I have two other courses I would recommend after this if you want
would recommend after this if you want to learn more about DAX. The first one
to learn more about DAX. The first one is just DAX functions in PowerBI. I'm
is just DAX functions in PowerBI. I'm listed down here as the collaborator. I
listed down here as the collaborator. I was basically the brains behind the
was basically the brains behind the scenes putting this course together. And
scenes putting this course together. And this goes into all the basics of DAX.
this goes into all the basics of DAX. When we get into iterating functions in
When we get into iterating functions in chapter 4 of this module or of this
chapter 4 of this module or of this course, that's when we start covering
course, that's when we start covering more new stuff that we didn't cover in
more new stuff that we didn't cover in here. The second course that I helped
here. The second course that I helped create was intermediate DAX and PowerBI.
create was intermediate DAX and PowerBI. This one has a lot of things in here
This one has a lot of things in here that we didn't even cover in this course
that we didn't even cover in this course that are frankly intermediate. Here I am
that are frankly intermediate. Here I am listed as collaborator down here.
listed as collaborator down here. Anyway, this would also be a great
Anyway, this would also be a great option to dive into next if you want to
option to dive into next if you want to learn more with DAX. I may consider in
learn more with DAX. I may consider in the future building a second PowerBI
the future building a second PowerBI course, basically getting into advanced
course, basically getting into advanced DAXs and encompassing all these
DAXs and encompassing all these different other techniques. So, if
different other techniques. So, if you're interested that, let me know in
you're interested that, let me know in the comments below. Anyway, that was our
the comments below. Anyway, that was our last lesson of actually learning what to
last lesson of actually learning what to do with PowerBI. We're now going to be
do with PowerBI. We're now going to be jumping next into the final project,
jumping next into the final project, applying all those different concepts
applying all those different concepts we've learned, and building something
we've learned, and building something out super special. Oh, I forgot to
out super special. Oh, I forgot to mention you do have some practice
mention you do have some practice problems, your last set of practice
problems, your last set of practice problems to go through and test out
problems to go through and test out parameters with. Anyway, and with that,
parameters with. Anyway, and with that, actually, see you in the next one.
All right, welcome to this final section where we're going to be tackling our
where we're going to be tackling our last project. And this is going to be
last project. And this is going to be broken into two videos. First one is
broken into two videos. First one is actually building out our dashboard and
actually building out our dashboard and the second one is getting into my
the second one is getting into my recommended ways for sharing it. Now,
recommended ways for sharing it. Now, I'm going to start with this. You can
I'm going to start with this. You can feel free to follow along in this video
feel free to follow along in this video and build out the recommendations that
and build out the recommendations that I'm going to recommend for building out
I'm going to recommend for building out our second project, but I highly
our second project, but I highly recommend that instead you if you want
recommend that instead you if you want to, you can watch it, but I recommend
to, you can watch it, but I recommend just skipping it and you dive deep and
just skipping it and you dive deep and build out your own dashboard that you
build out your own dashboard that you find usable and beneficial to you. Truth
find usable and beneficial to you. Truth be told, I'm not going to be there
be told, I'm not going to be there holding your hand in the real world,
holding your hand in the real world, guiding you along on what you need to
guiding you along on what you need to do. So, you need to take the initiative
do. So, you need to take the initiative now and start coming up with ideas on
now and start coming up with ideas on how you can actually build effective
how you can actually build effective visualizations. So, with that, I'm going
visualizations. So, with that, I'm going to provide first some constructive
to provide first some constructive feedback on our last project. That way,
feedback on our last project. That way, it can maybe inspire some ideas on what
it can maybe inspire some ideas on what you could build out. Then, from there,
you could build out. Then, from there, I'm going to build out what I want to
I'm going to build out what I want to actually build.
So, let's get back into some feedback that I have on this first dashboard. And
that I have on this first dashboard. And as a reminder, remember it was two
as a reminder, remember it was two pages. We have our first actual landing
pages. We have our first actual landing page dashboard, and then in the second
page dashboard, and then in the second page, we're allowed to drill through
page, we're allowed to drill through into particular job titles so we can
into particular job titles so we can dive deeper into insights. Anyway, I've
dive deeper into insights. Anyway, I've been using this bad boy while going
been using this bad boy while going through and building this course, and I
through and building this course, and I have some thoughts on things I want to
have some thoughts on things I want to improve on it based on my real world
improve on it based on my real world experience with implementing dashboards.
experience with implementing dashboards. Anyway, the first thing is this. The
Anyway, the first thing is this. The KPIs, specifically those cards up at the
KPIs, specifically those cards up at the top on the main dashboard, are really
top on the main dashboard, are really beneficial. I really like them, and I
beneficial. I really like them, and I like that they provide value immediately
like that they provide value immediately to me on what I'm looking for. Now,
to me on what I'm looking for. Now, regarding all the other visualizations,
regarding all the other visualizations, they're great, but I particularly like
they're great, but I particularly like the visuals on hourly and yearly salary.
the visuals on hourly and yearly salary. This scatter plot, not going to lie,
This scatter plot, not going to lie, it's a little hard to read, but I do
it's a little hard to read, but I do like down here these different plots or
like down here these different plots or these different charts we've implemented
these different charts we've implemented into our matrix to show this. We don't
into our matrix to show this. We don't need to necessarily do it like this, but
need to necessarily do it like this, but maybe we could use parameters to build
maybe we could use parameters to build something with this. Here's some other
something with this. Here's some other areas that I want to tweak. The KPIs or
areas that I want to tweak. The KPIs or the cards I said I did like, but that
the cards I said I did like, but that average job rating, it's very unclear on
average job rating, it's very unclear on what actually is going on there. and
what actually is going on there. and frankly is biased to what I had set up
frankly is biased to what I had set up for this fivestar system. Also looking
for this fivestar system. Also looking at it holistically with the main page
at it holistically with the main page and also with that drill through page,
and also with that drill through page, there's just too many visuals for my
there's just too many visuals for my liking. I want to drill it down to only
liking. I want to drill it down to only the core visuals necessary. And although
the core visuals necessary. And although the drill through feature was really
the drill through feature was really nice and fancy, in my practice, I'm not
nice and fancy, in my practice, I'm not seeing it getting used as much unless
seeing it getting used as much unless you're actually training your users on
you're actually training your users on it. So here are my top features that I
it. So here are my top features that I definitely want to include on this. I
definitely want to include on this. I want to focus on two things mainly
want to focus on two things mainly skills and then salary of jobs. For the
skills and then salary of jobs. For the skill data I want to show pre like we
skill data I want to show pre like we showed previously the counts but also it
showed previously the counts but also it in a relative percentage like how many
in a relative percentage like how many jobs are requesting Python. And then for
jobs are requesting Python. And then for the salary I want to do this for job
the salary I want to do this for job titles and I want to be able to easily
titles and I want to be able to easily flip between analyzing for hourly or
flip between analyzing for hourly or yearly. Now, the last two things are
yearly. Now, the last two things are things that I've actually gotten
things that I've actually gotten insights from this website of my dad.te
insights from this website of my dad.te and that was this country filter was a
and that was this country filter was a really big demand in my subscribers. I
really big demand in my subscribers. I initially when I built this didn't have
initially when I built this didn't have this and everybody was commenting
this and everybody was commenting include a country filter. Also, I really
include a country filter. Also, I really like the well the aesthetics of this
like the well the aesthetics of this specifically how it's more of a dark
specifically how it's more of a dark theme with it. So, that's the last two
theme with it. So, that's the last two things. We're going to add a country
things. We're going to add a country slicer and also we're going to be using
slicer and also we're going to be using dark mode.
So, let's get into rough drafting out this dashboard. As a reminder, you're
this dashboard. As a reminder, you're following along with me. Completely
following along with me. Completely optional. However you want to do it,
optional. However you want to do it, feel free to do it and modify as
feel free to do it and modify as necessary. Anyway, in the first
necessary. Anyway, in the first dashboard that we built, I actually
dashboard that we built, I actually physically wrote this out. Yeah, I know
physically wrote this out. Yeah, I know this is my bad handwriting. And I
this is my bad handwriting. And I actually physically drew this out, but I
actually physically drew this out, but I don't always do this. Instead, I like to
don't always do this. Instead, I like to sometimes just play around in PowerBI
sometimes just play around in PowerBI shaping things and rough drafting it
shaping things and rough drafting it that way. So, that's what we're going to
that way. So, that's what we're going to do for this one. For this, you can start
do for this one. For this, you can start off with the file that we used in the
off with the file that we used in the last lesson, which if you got lost along
last lesson, which if you got lost along the way, just go into that DAX folder is
the way, just go into that DAX folder is that last one of parameters. We want to
that last one of parameters. We want to use that same data model that we created
use that same data model that we created previously. And so all of that different
previously. And so all of that different work we're going to keep. I'm just going
work we're going to keep. I'm just going to end up getting rid of all these
to end up getting rid of all these different sheets towards the end.
different sheets towards the end. Anyway, I'm going to start a new page
Anyway, I'm going to start a new page here and call it data jobs 2.0. Now,
here and call it data jobs 2.0. Now, we're going to be implementing a dark
we're going to be implementing a dark theme on this. So, I'm going to go ahead
theme on this. So, I'm going to go ahead actually right now into view and under
actually right now into view and under themes I'm going to change it to I
themes I'm going to change it to I really like this theme right here, this
really like this theme right here, this innovate. And I'm going to change it to
innovate. And I'm going to change it to this. But I'll be honest, this isn't
this. But I'll be honest, this isn't dark theme enough for me specifically. I
dark theme enough for me specifically. I want to work in a dark theme too, too.
want to work in a dark theme too, too. So, going into files and under options
So, going into files and under options and settings and options, we can go into
and settings and options, we can go into report settings and I'm going to
report settings and I'm going to actually change my layout from this
actually change my layout from this portion to a dark theme. Bam. All right.
portion to a dark theme. Bam. All right. Now we're ready to build with dark
Now we're ready to build with dark theme. So remember my two main areas
theme. So remember my two main areas that I want on this on features. I want
that I want on this on features. I want one area or one half focusing on skills
one area or one half focusing on skills and then the other half focusing on
and then the other half focusing on salary. So I'm going to put two visuals
salary. So I'm going to put two visuals on there to get started. Personally I
on there to get started. Personally I prioritize skills over salary because
prioritize skills over salary because you need the skills to get the salary.
you need the skills to get the salary. So stealing this from our skills stats
So stealing this from our skills stats page that we built. I'm gonna take this
page that we built. I'm gonna take this visual, control C, and then put this in
visual, control C, and then put this in here. I'm going to lower it some because
here. I'm going to lower it some because like you like before, we want a great
like you like before, we want a great design layout where we have the KPIs up
design layout where we have the KPIs up at top and then the visuals below. Other
at top and then the visuals below. Other thing is I want to make sure this is
thing is I want to make sure this is centered. All right, looking good. Next
centered. All right, looking good. Next thing I want is remember those salaries.
thing I want is remember those salaries. And for this one, I'm going to use that
And for this one, I'm going to use that new measure check page that we have
new measure check page that we have created right here. And I'm going to
created right here. And I'm going to copy this one down here that has all
copy this one down here that has all these different ones in here. And then
these different ones in here. And then paste it in. I'm not realizing I should
paste it in. I'm not realizing I should have got the skills one from there, too,
have got the skills one from there, too, because right now this job count isn't
because right now this job count isn't using our measure that we created. So,
using our measure that we created. So, I'm going to actually delete that out of
I'm going to actually delete that out of there and drag job count into here. And
there and drag job count into here. And then update that y-axis to say skill.
then update that y-axis to say skill. All right. So, remember, I'm just rough
All right. So, remember, I'm just rough drafting right now. I do want KPIs on
drafting right now. I do want KPIs on top of here. So, we're going to be using
top of here. So, we're going to be using that card new. Make sure you don't
that card new. Make sure you don't select the actual visual and do this.
select the actual visual and do this. I'm I'm going control Z this. I didn't
I'm I'm going control Z this. I didn't have the outside selected. I'm insert in
have the outside selected. I'm insert in card new and I'm going to drag this
card new and I'm going to drag this along this top area right here. We're
along this top area right here. We're going to put titles and slicers up at
going to put titles and slicers up at the top. So that's why I'm going to
the top. So that's why I'm going to leave that space. Now in this I'm going
leave that space. Now in this I'm going to have four different KPIs. I want the
to have four different KPIs. I want the leftmost to deal with well like counts
leftmost to deal with well like counts and skills. So I'm going to drag job
and skills. So I'm going to drag job count into here and then also skills per
count into here and then also skills per job. And then over on top of this one,
job. And then over on top of this one, don't worry, this is going to shift over
don't worry, this is going to shift over as soon as you add more. Over on top of
as soon as you add more. Over on top of this one, I want things like the yearly
this one, I want things like the yearly and then also hourly salary. So I'll
and then also hourly salary. So I'll drag median yearly salary in. I notice
drag median yearly salary in. I notice also that we don't have anything for
also that we don't have anything for hourly. So what I'm going to do is going
hourly. So what I'm going to do is going to copy the median yearly salary. Right
to copy the median yearly salary. Right click, create a new measure. Paste this
click, create a new measure. Paste this one in. Replace everything for hourly.
one in. Replace everything for hourly. And everything is updated. Press enter.
And everything is updated. Press enter. And now going and dragging in median
And now going and dragging in median hourly salary with that slicer selected.
hourly salary with that slicer selected. Only three things are showing. That's
Only three things are showing. That's because under format your visual the
because under format your visual the layout right now it says max card shown
layout right now it says max card shown three. We want to bump that up to four.
three. We want to bump that up to four. I also don't like this border around
I also don't like this border around each of those cards. So I'm going to
each of those cards. So I'm going to select border or type in border. And
select border or type in border. And then underneath cards I see that that's
then underneath cards I see that that's the border that I want. I'm going to
the border that I want. I'm going to undo it. I also don't like how these are
undo it. I also don't like how these are not centered. They're all left aligned.
not centered. They're all left aligned. So, inside of callout values, I'm going
So, inside of callout values, I'm going to go down here and just center those.
to go down here and just center those. All right, not too bad. Let's insert in
All right, not too bad. Let's insert in a title and some put put some slicers up
a title and some put put some slicers up at the top. Put in data jobs dashboard
at the top. Put in data jobs dashboard 2.0. Made it a 36 point font and then
2.0. Made it a 36 point font and then put it in bold. All right. Now, let's
put it in bold. All right. Now, let's add in some slicers. Remember, we want
add in some slicers. Remember, we want to slice two things. We want to slice
to slice two things. We want to slice that job title short and then also the
that job title short and then also the country. But let's actually format this
country. But let's actually format this one how we actually want it to look. and
one how we actually want it to look. and then we'll copy it. Specifically under
then we'll copy it. Specifically under format visual, the style, we're going to
format visual, the style, we're going to change this to a drop down. I'm also
change this to a drop down. I'm also going to make the values a little bit
going to make the values a little bit bigger so that way you can see it. Go
bigger so that way you can see it. Go size 14. Inside of here, I want a few
size 14. Inside of here, I want a few different options. Specifically, the
different options. Specifically, the selection, I want to show select all.
selection, I want to show select all. So, I'm going to enable that. And then
So, I'm going to enable that. And then in the slicer itself, clicking the three
in the slicer itself, clicking the three dots, I'm going to enable search. That
dots, I'm going to enable search. That way whenever they drop down here, they
way whenever they drop down here, they can actually have be able to search for
can actually have be able to search for something like data analyst. They can
something like data analyst. They can select it, it'll filter. All right, undo
select it, it'll filter. All right, undo it. The last thing is I like to cue
it. The last thing is I like to cue people in. So I'm just going to say
people in. So I'm just going to say select job title. Okay, looking good.
select job title. Okay, looking good. Let's actually copy this. And in this
Let's actually copy this. And in this one, instead of doing select job title,
one, instead of doing select job title, we're going to drag in job country. And
we're going to drag in job country. And we'll rename this to select country.
we'll rename this to select country. Now, I do want an easy way to clear the
Now, I do want an easy way to clear the slicers. So, I am going to insert a
slicers. So, I am going to insert a button. Specifically, we're going to
button. Specifically, we're going to insert a clear all slicers button. And
insert a clear all slicers button. And I'm going to put it over here to the
I'm going to put it over here to the right hand side. Under the button
right hand side. Under the button option, going to style. I'm just going
option, going to style. I'm just going to say instead of clear all slicers,
to say instead of clear all slicers, only two. I'm just say clear slicers.
only two. I'm just say clear slicers. Also, make that text a little bit
Also, make that text a little bit bigger. And I'm going to enable the
bigger. And I'm going to enable the shadow to make it look a little bit more
shadow to make it look a little bit more standout so people understand it is a
standout so people understand it is a button. I do have to format things a
button. I do have to format things a little bit to make a little bit more
little bit to make a little bit more space for it. All right. Looking good.
space for it. All right. Looking good. I'm liking this layout here. It's very
I'm liking this layout here. It's very simple. We got two visuals underneath.
simple. We got two visuals underneath. We got our main KPIs up at the top and
We got our main KPIs up at the top and then we have the appropriate slicers as
then we have the appropriate slicers as well.
All right. Now that we have the rough draft out of the way, there is some
draft out of the way, there is some refinement I want to get into with this.
refinement I want to get into with this. Specifically, as I mentioned in the
Specifically, as I mentioned in the beginning, for these skills, I want to
beginning, for these skills, I want to look at it from two perspectives. Job
look at it from two perspectives. Job count and percentage. And then for the
count and percentage. And then for the salary, I want to look at it from yearly
salary, I want to look at it from yearly and also hourly. I want to be able to
and also hourly. I want to be able to switch between them. We need to do
switch between them. We need to do parameters for this. Let's get into the
parameters for this. Let's get into the skill one first. Specifically, we want a
skill one first. Specifically, we want a percentage. What do I mean by
percentage. What do I mean by percentage? Well, in my app, I don't
percentage? Well, in my app, I don't present counts of a particular skill.
present counts of a particular skill. Instead, what a percent is the
Instead, what a percent is the percentage or likelihood that it's going
percentage or likelihood that it's going to be in a job posting. In this case,
to be in a job posting. In this case, Python is in 55% of all job postings.
Python is in 55% of all job postings. Whenever I filter for something like
Whenever I filter for something like data analyst in the United States, it
data analyst in the United States, it tells me something like PowerBI is in
tells me something like PowerBI is in almost 17% of job postings. So, we need
almost 17% of job postings. So, we need to create a measure inside of PowerBI to
to create a measure inside of PowerBI to do this skill percentage before we even
do this skill percentage before we even create that parameter. So, I'm going to
create that parameter. So, I'm going to rightclick our measures and select
rightclick our measures and select create new measure. In this, we're going
create new measure. In this, we're going to create a new one called job percent.
to create a new one called job percent. Now, in order to get this percentage, we
Now, in order to get this percentage, we have to take well, we have to divide. We
have to take well, we have to divide. We have to have a numerator and a
have to have a numerator and a denominator. So we're going to use the
denominator. So we're going to use the divide function for this. So the
divide function for this. So the numerator is the count of a particular
numerator is the count of a particular skill that has been filtered down into
skill that has been filtered down into the correct context. So in the case of
the correct context. So in the case of something like Python that's below here,
something like Python that's below here, that is the count of Python, which is
that is the count of Python, which is 244,000. Anyway, that's done by the
244,000. Anyway, that's done by the measure job count. So that's pretty
measure job count. So that's pretty easy, right? We just put in job count.
easy, right? We just put in job count. But now the denominator,
But now the denominator, this needs to be basically this job
this needs to be basically this job count right here, this 479,000.
count right here, this 479,000. But I can't just put something in like
But I can't just put something in like job count, right? Um cuz this isn't
job count, right? Um cuz this isn't going to show the right context. I'm
going to show the right context. I'm just doing this for demonstration
just doing this for demonstration purposes. I'm dividing job count by job
purposes. I'm dividing job count by job count. And then inside of here, I'm
count. And then inside of here, I'm going to drag job percentage in here and
going to drag job percentage in here and take off job count. Anyway, every single
take off job count. Anyway, every single one of them, right, is 100% not what we
one of them, right, is 100% not what we want. So, going to job percentage just
want. So, going to job percentage just to show what we do need in here. We need
to show what we do need in here. We need it to be basically that 479,000 of
it to be basically that 479,000 of 479,000. We're not going to keep this
479,000. We're not going to keep this cuz we could potentially put filters on
cuz we could potentially put filters on it. I'm going to show you why. Anyway,
it. I'm going to show you why. Anyway, pressing uh enter to do this. See, this
pressing uh enter to do this. See, this looks very similar to what we saw
looks very similar to what we saw previously. And I know this is correct
previously. And I know this is correct because it has the same around 51%.
because it has the same around 51%. That's what I expected to be see for
That's what I expected to be see for Python and SQL. Right now, it's not in
Python and SQL. Right now, it's not in the right format. So, I'm actually going
the right format. So, I'm actually going to select it. I'm going to change this
to select it. I'm going to change this to a percentage with zero decimal
to a percentage with zero decimal places. Anyway, I digress. So, with this
places. Anyway, I digress. So, with this job percentage, how are we going to get
job percentage, how are we going to get this correct value in here? Because
this correct value in here? Because right now, if I were to now filter for
right now, if I were to now filter for something like data analyst and then go
something like data analyst and then go down, right, this number has now changed
down, right, this number has now changed to 113,000. So, I can't hardcode it in.
to 113,000. So, I can't hardcode it in. These percentages are not correct.
These percentages are not correct. they're entirely too low. We need to
they're entirely too low. We need to basically use a certain function that
basically use a certain function that will remove that query context. This is
will remove that query context. This is why it's important that you know between
why it's important that you know between row query and filter context. Going into
row query and filter context. Going into job percent, you know, we're probably
job percent, you know, we're probably going to use something like the
going to use something like the calculate function for this. And for the
calculate function for this. And for the expression, we're still going to use job
expression, we're still going to use job count, but we want to do something in
count, but we want to do something in order to remove this skill context
order to remove this skill context filter or this skill query context
filter or this skill query context filter that's on there. Well, lucky for
filter that's on there. Well, lucky for us, there's a function for that called
us, there's a function for that called all selected. This removes the filters
all selected. This removes the filters from columns and rows in the current
from columns and rows in the current query. In our case, those column and
query. In our case, those column and rows would be the visualization.
rows would be the visualization. And with this, it retains all other
And with this, it retains all other context filters or explicit filters. So,
context filters or explicit filters. So, we need to specify what filters we don't
we need to specify what filters we don't want it to actually filter down for. And
want it to actually filter down for. And specifically, we don't want to filter
specifically, we don't want to filter down for this skills. So, I'm going to
down for this skills. So, I'm going to put in all selected. And we can put in a
put in all selected. And we can put in a table name or column. We need to put the
table name or column. We need to put the name of the column or name of the table
name of the column or name of the table where the skills are. So, skill dim. All
where the skills are. So, skill dim. All right. Now, pressing enter. Boom. This
right. Now, pressing enter. Boom. This data analyst actually updated and it's
data analyst actually updated and it's where I suspect, right? PowerBI here is
where I suspect, right? PowerBI here is up to 23%. Notice this is going to be
up to 23%. Notice this is going to be different from our dashboard or data
different from our dashboard or data nerd.te because data nerd.tech has
nerd.te because data nerd.tech has multiple different years. We're only
multiple different years. We're only doing 2024 within this dashboard, but
doing 2024 within this dashboard, but the percentages are very similar.
the percentages are very similar. Anyway, if I wanted to doublech check
Anyway, if I wanted to doublech check this, I could inside this visualization
this, I could inside this visualization in the tool tip drag in that job count
in the tool tip drag in that job count and then I could double check the math
and then I could double check the math by saying that hey, is 26500
by saying that hey, is 26500 / 113 23%. It is. I did the math just in
/ 113 23%. It is. I did the math just in case you don't believe me. All right,
case you don't believe me. All right, sweet. Let's go ahead and remove this
sweet. Let's go ahead and remove this data analyst filter. And let's now since
data analyst filter. And let's now since we have we have our job percentage and
we have we have our job percentage and job count for this one and our median,
job count for this one and our median, yearly, and median hourly, we need to
yearly, and median hourly, we need to create our parameters for this because
create our parameters for this because we're going to have slicers or basically
we're going to have slicers or basically tile buttons below this to select what
tile buttons below this to select what kind of view we want to see with each
kind of view we want to see with each within each of these. So, inside
within each of these. So, inside modeling, I'm going to go to new
modeling, I'm going to go to new parameters and we're going to do fields.
parameters and we're going to do fields. And for this, we're going to say select
And for this, we're going to say select skill measure. And I'm going to drag in
skill measure. And I'm going to drag in job percent first because I feel that's
job percent first because I feel that's more important. And then they can also,
more important. And then they can also, if they want to switch to job count, and
if they want to switch to job count, and I'm going to go ahead and select create
I'm going to go ahead and select create with add slicer to this page. I'm going
with add slicer to this page. I'm going to drag it down to this bottom portion
to drag it down to this bottom portion right here. I'm going to change this
right here. I'm going to change this slicer though. I don't want it to be a
slicer though. I don't want it to be a vertical list. I want it to be actual
vertical list. I want it to be actual tile buttons. And I don't like the title
tile buttons. And I don't like the title on there. I don't want it to have a
on there. I don't want it to have a title on there. So, I'm actually going
title on there. So, I'm actually going to click on here, just press space, and
to click on here, just press space, and then press enter to remove it. And then
then press enter to remove it. And then reformat this other visual to be right
reformat this other visual to be right above this. Okay. So, now I can select
above this. Okay. So, now I can select things like job percent or job count.
things like job percent or job count. And it's doing nothing because it's not
And it's doing nothing because it's not in our visual. So, with our visual
in our visual. So, with our visual selected, I'm go under select scale
selected, I'm go under select scale measure, and I'm going to drag that into
measure, and I'm going to drag that into the X-axis and remove this job percent.
the X-axis and remove this job percent. Okay. So, now I can switch between job
Okay. So, now I can switch between job percent and job count. and the
percent and job count. and the proportions of these should remain the
proportions of these should remain the same. So that's how you can also double
same. So that's how you can also double check that your math is right. Anyway,
check that your math is right. Anyway, let's do the same thing now for this
let's do the same thing now for this graph where we want to create a
graph where we want to create a parameter for hourly and yearly salary.
parameter for hourly and yearly salary. So I'm going to create a new fields
So I'm going to create a new fields parameter and I'll say select job
parameter and I'll say select job measure. I want yearly salary first
measure. I want yearly salary first followed by hourly. We're going to go
followed by hourly. We're going to go create this. It's going to add in a
create this. It's going to add in a slicer. Similarly, I'm going to remove
slicer. Similarly, I'm going to remove the title by selecting all of this in
the title by selecting all of this in the fields well pressing space and then
the fields well pressing space and then enter. And then under format your visual
enter. And then under format your visual under slicer settings. I'm going to
under slicer settings. I'm going to change this to tile. Once again, this
change this to tile. Once again, this isn't going to do anything till we
isn't going to do anything till we actually add it into our visualization
actually add it into our visualization itself. Just going to drag this in here
itself. Just going to drag this in here to the x-axis and get rid of that median
to the x-axis and get rid of that median yearly salary. And now we can select
yearly salary. And now we can select between the two. Pretty neat. Also, I'm
between the two. Pretty neat. Also, I'm noticing our median hourly salary is not
noticing our median hourly salary is not formatted correctly as currency. And
formatted correctly as currency. And we're just going to keep it simple at
we're just going to keep it simple at zero decimal places.
zero decimal places. All
All right, this is looking pretty sweet. I'm
right, this is looking pretty sweet. I'm liking it. But I do want to do some
liking it. But I do want to do some elements of improving the background to
elements of improving the background to show how this actually all works
show how this actually all works together cuz right now it's really
together cuz right now it's really unclear that the parameters work with
unclear that the parameters work with these graphs above here. So we can build
these graphs above here. So we can build in v visual cues in the background that
in v visual cues in the background that they are associated with each other
they are associated with each other along with these KPIs as well. We're
along with these KPIs as well. We're going to follow a similar similar
going to follow a similar similar approach that we did in the last
approach that we did in the last project. And I'm just going to use these
project. And I'm just going to use these rounded rectangles that we're going to
rounded rectangles that we're going to end up putting in the back. First thing
end up putting in the back. First thing I'm going to do is actually put these
I'm going to do is actually put these around the appropriate KPIs. So, we'll
around the appropriate KPIs. So, we'll do each of these. But let's actually I'm
do each of these. But let's actually I'm getting ahead of myself. We need to
getting ahead of myself. We need to adjust the coloring first. I don't want
adjust the coloring first. I don't want this blue color. So, under the format
this blue color. So, under the format shape, I'm going to the style. And then
shape, I'm going to the style. And then for the color first, I want to match the
for the color first, I want to match the background exactly. And I'm actually
background exactly. And I'm actually fine. I can't match the background
fine. I can't match the background exactly, but what I want is I want it to
exactly, but what I want is I want it to be slightly darker. So, I went with
be slightly darker. So, I went with black 20% lighter. And I don't know if
black 20% lighter. And I don't know if you can see, but there's like this blue
you can see, but there's like this blue line around here. Specifically, those
line around here. Specifically, those borders on. And for this one, I'm going
borders on. And for this one, I'm going to make it even slightly darker. To make
to make it even slightly darker. To make it stand out and pop and make it pop
it stand out and pop and make it pop even more, I'm going to turn on shadows.
even more, I'm going to turn on shadows. All right. So, this is good enough. I'm
All right. So, this is good enough. I'm going to now copy this and then paste
going to now copy this and then paste this for this KPI as well. And then I'm
this for this KPI as well. And then I'm going to create two more for these
going to create two more for these visualizations. Now, with these
visualizations. Now, with these visualizations, it's getting these extra
visualizations, it's getting these extra rounded curves. I don't really like
rounded curves. I don't really like that. So, I'm going to go under shape
that. So, I'm going to go under shape and the rounded corners. I'm going to
and the rounded corners. I'm going to just going to bring down until it
just going to bring down until it matches the rounded shape of that above
matches the rounded shape of that above it. It's around 10%. All right, looks
it. It's around 10%. All right, looks good. Going to copy this one. Going to
good. Going to copy this one. Going to paste it. Not bad. Like last time, I
paste it. Not bad. Like last time, I want to group all these and put them in
want to group all these and put them in the back. So, we need to go into that
the back. So, we need to go into that view, specifically showing the
view, specifically showing the selection. I'm going minimize this. So,
selection. I'm going minimize this. So, this is showing all of our different
this is showing all of our different shapes. I'm going to select all of our
shapes. I'm going to select all of our appropriate shapes by holding control,
appropriate shapes by holding control, selecting them all. Now, they're
selecting them all. Now, they're selected. Rightclick them, go to group,
selected. Rightclick them, go to group, name this group background, and then put
name this group background, and then put it all the way in the back. But we can't
it all the way in the back. But we can't see it, right? So, we need to remove for
see it, right? So, we need to remove for each one of these visuals, we need to
each one of these visuals, we need to remove their backgrounds or make it
remove their backgrounds or make it transparent. So, I'm going to turn off
transparent. So, I'm going to turn off the selection pane. We're done with that
the selection pane. We're done with that now. And get back into visualizations.
now. And get back into visualizations. We're going to go into these visuals and
We're going to go into these visuals and specifically under the format your
specifically under the format your visual under general under effects,
visual under general under effects, we're going to remove the background.
we're going to remove the background. And then for these cards is a little bit
And then for these cards is a little bit more complex. You actually have to go
more complex. You actually have to go into cards as well on top of what you
into cards as well on top of what you just did and then select background and
just did and then select background and turn this off. Anyway, now need to
turn this off. Anyway, now need to adjust these. Well, at least not the KPI
adjust these. Well, at least not the KPI cards. Those are fitting just fine
cards. Those are fitting just fine inside of there. But we need to adjust
inside of there. But we need to adjust now these visuals to make sure that
now these visuals to make sure that they're fitting inside of these
they're fitting inside of these appropriate blocks. All right, not
appropriate blocks. All right, not looking bad. This is now finalized. The
looking bad. This is now finalized. The next thing that I'd want to do is
next thing that I'd want to do is hopefully you've been saving this along
hopefully you've been saving this along the way. If you haven't, now is a good
the way. If you haven't, now is a good time to save it. But I'm going to
time to save it. But I'm going to actually save this with a new title so I
actually save this with a new title so I can get rid of all these different
can get rid of all these different pages. And then we can upload it to the
pages. And then we can upload it to the PowerBI service if you happen to want to
PowerBI service if you happen to want to do that option. Not required by any
do that option. Not required by any means. I'm going to call this data jobs
means. I'm going to call this data jobs dashboard 2.0 and then go through and
dashboard 2.0 and then go through and remove all these extra pages in here.
remove all these extra pages in here. Okay, everything's in here that I want.
Okay, everything's in here that I want. I'm going to save it again. And then
I'm going to save it again. And then under the home tag, I can go into
under the home tag, I can go into publish, select the dashboard I want to
publish, select the dashboard I want to go to, and click select and upload it.
go to, and click select and upload it. So, here's mine uploaded onto the
So, here's mine uploaded onto the PowerBI service. I can go through if I
PowerBI service. I can go through if I want to select things like data analyst
want to select things like data analyst in the United States and bam. This thing
in the United States and bam. This thing is good. I'm liking it. Remember if you
is good. I'm liking it. Remember if you did take this option or do this option
did take this option or do this option you can go to the option of under file
you can go to the option of under file embedded report and then publish to web
embedded report and then publish to web and then you'll get this link which you
and then you'll get this link which you can actually view mine at the link below
can actually view mine at the link below and this is accessible from any URL and
and this is accessible from any URL and completely interactive like we showed
completely interactive like we showed previously. Anyway, now I think we have
previously. Anyway, now I think we have the dashboard in a much better manner.
the dashboard in a much better manner. This meets all the things that I wanted
This meets all the things that I wanted out of this specifically. I wanted to
out of this specifically. I wanted to have insights on the skills. what were
have insights on the skills. what were the top skills and then also with the
the top skills and then also with the salaries, what were basically the
salaries, what were basically the highest paying jobs hourly and also
highest paying jobs hourly and also yearly. And for cases where we want to
yearly. And for cases where we want to filter our data down, such as looking at
filter our data down, such as looking at something like the data analyst, we can
something like the data analyst, we can get even more insights and value out of
get even more insights and value out of things like the KPIs above here.
things like the KPIs above here. Overall, I'm pretty in love with this
Overall, I'm pretty in love with this dashboard. Now, it's your turn to go
dashboard. Now, it's your turn to go through and finalize your project. Once
through and finalize your project. Once again, as a reminder, you're not
again, as a reminder, you're not required to follow my project exactly.
required to follow my project exactly. feel free to adapt it to your need.
feel free to adapt it to your need. Anyway, in the next lesson, the final
Anyway, in the next lesson, the final lesson, we're going to get into how I
lesson, we're going to get into how I would go about sharing this dashboard
would go about sharing this dashboard along with that previous dashboard that
along with that previous dashboard that we created halfway through this course.
we created halfway through this course. With that, see you in the next one.
All right, first of all, congratulations on wrapping up the second project and
on wrapping up the second project and now, if you will, this entire course.
now, if you will, this entire course. It's been nothing short of your hard
It's been nothing short of your hard work. In this video, we're going to be
work. In this video, we're going to be going through how to actually better
going through how to actually better share both of those different portfolio
share both of those different portfolio projects that we put together. But for
projects that we put together. But for our most recent dashboard, we still need
our most recent dashboard, we still need to go through and create a readme to
to go through and create a readme to document what we all did. And as we're
document what we all did. And as we're going to find out, we need to reorganize
going to find out, we need to reorganize our project. Anyway, what do I mean by
our project. Anyway, what do I mean by that? Let's jump in.
So, here I am inside of VS Code and we haven't changed anything since the last
haven't changed anything since the last left off. But specifically inside of our
left off. But specifically inside of our PowerBI dashboards, we have three
PowerBI dashboards, we have three different objects. Images folder, the
different objects. Images folder, the data jobs dashboard or actual PowerBI
data jobs dashboard or actual PowerBI file, and then our readme. I can even
file, and then our readme. I can even pull it up on VS Code just to show that
pull it up on VS Code just to show that okay it is these three things and that
okay it is these three things and that readme is getting put on that first page
readme is getting put on that first page and that's for this project or this repo
and that's for this project or this repo that we have of PowerBI dashboards but I
that we have of PowerBI dashboards but I want all of our projects in here or our
want all of our projects in here or our la or our current two projects in here.
la or our current two projects in here. So we need to restructure this in a way
So we need to restructure this in a way to accomplish that. So back inside of VS
to accomplish that. So back inside of VS Code, what I'm going to do is I'm going
Code, what I'm going to do is I'm going to create a folder for these projects
to create a folder for these projects right here. I'm going to call it data
right here. I'm going to call it data jobs v1. Press enter. Anyway, I'm going
jobs v1. Press enter. Anyway, I'm going to grab these both these items and put
to grab these both these items and put them inside of here. Now, with this
them inside of here. Now, with this restructuring,
restructuring, unfortunately, we don't have something
unfortunately, we don't have something to deh show on the front of our repo.
to deh show on the front of our repo. But now, with this restructuring, it's
But now, with this restructuring, it's going to affect how our repo looks.
going to affect how our repo looks. Specifically, I'm just going to show
Specifically, I'm just going to show this for demo. You don't need to do
this for demo. You don't need to do this. I'm going to push these changes up
this. I'm going to push these changes up to GitHub with this commit of move
to GitHub with this commit of move folders commit. and then I'm going to
folders commit. and then I'm going to sync the changes. Now, refreshing this
sync the changes. Now, refreshing this inside of GitHub, what we're going to
inside of GitHub, what we're going to notice is, okay, we got our folder, but
notice is, okay, we got our folder, but now we need a readme. So, what we're
now we need a readme. So, what we're going to do is we're going to create a
going to do is we're going to create a readme for the top of the repository and
readme for the top of the repository and then direct people to either data jobs
then direct people to either data jobs v1 and data jobs v2. And if you happen
v1 and data jobs v2. And if you happen to make other projects in PowerBI, you
to make other projects in PowerBI, you can just add them straight to this. So,
can just add them straight to this. So, super convenient. So, back in VS Code
super convenient. So, back in VS Code under explore, I'm going to go ahead and
under explore, I'm going to go ahead and add a new file. And this one is going to
add a new file. And this one is going to be called readme.md. Now, these readmes,
be called readme.md. Now, these readmes, right, they need to be named this
right, they need to be named this specifically because that's how GitHub
specifically because that's how GitHub knows to pick it up and display it. I'm
knows to pick it up and display it. I'm going to close this side pane and also
going to close this side pane and also zoom out a little bit. I'm pressing
zoom out a little bit. I'm pressing control and then minus. All right, so
control and then minus. All right, so let's go ahead and build out this front
let's go ahead and build out this front page. And we're going to keep it really
page. And we're going to keep it really simple. I'm also going to be opening up
simple. I'm also going to be opening up this side pane so we can see as we work
this side pane so we can see as we work as we go. I started off simple with my
as we go. I started off simple with my PowerBI dashboard portfolio. give a
PowerBI dashboard portfolio. give a little short intro into what I'm doing
little short intro into what I'm doing here. And then underneath this, I have a
here. And then underneath this, I have a featured dashboard section, which we can
featured dashboard section, which we can now list all of our different
now list all of our different dashboards. I'm going start by first
dashboards. I'm going start by first putting in that data jobs dashboard,
putting in that data jobs dashboard, this V1. We're going to just put an
this V1. We're going to just put an image in real quick. And we're going to
image in real quick. And we're going to use that same image we've been using
use that same image we've been using that we have in our image folders. And
that we have in our image folders. And for this I start by giving the
for this I start by giving the hypertext. So an exclamation point and
hypertext. So an exclamation point and then inside brackets a brackets the
then inside brackets a brackets the actual alt text and then in parentheses
actual alt text and then in parentheses the link to that specifically we want to
the link to that specifically we want to go in the images folder and we want that
go in the images folder and we want that project one page one. Now for me I'm
project one page one. Now for me I'm also going to list right underneath this
also going to list right underneath this the link to this so that way if they
the link to this so that way if they wanted to they can go to my interactive
wanted to they can go to my interactive dashboard that's hosted on the PowerBI
dashboard that's hosted on the PowerBI service. Now, the next section that I'm
service. Now, the next section that I'm going to add is optional, but highly
going to add is optional, but highly recommended. I'm going to capture in
recommended. I'm going to capture in bullet point, very succinctly, what are
bullet point, very succinctly, what are all the different PowerBI skills that I
all the different PowerBI skills that I used in order to build this
used in order to build this visualization. And then right under
visualization. And then right under this, I want to link them to my readme
this, I want to link them to my readme in the project one folder. So, they
in the project one folder. So, they start checking out this. So, we're going
start checking out this. So, we're going to create a link. In square brackets,
to create a link. In square brackets, I'm going to put what I want for the
I'm going to put what I want for the text. And then from there, I'm going to
text. And then from there, I'm going to put in the link. So whenever they go to
put in the link. So whenever they go to click on it, it will pop up and then
click on it, it will pop up and then they can go through that readme that we
they can go through that readme that we previously had. One note, I just put the
previously had. One note, I just put the skills that we previously had generated
skills that we previously had generated into CHBT, had it condensed down, and
into CHBT, had it condensed down, and that's how I got this list right here
that's how I got this list right here for our new readme. So we have the core
for our new readme. So we have the core features built out for this. I'm liking
features built out for this. I'm liking what's going on here. I'm going to now
what's going on here. I'm going to now save this and then close out of it all.
save this and then close out of it all. Go into source control and I'm going to
Go into source control and I'm going to push this up to my readme. Feel free to
push this up to my readme. Feel free to actually you do this now too as well. I
actually you do this now too as well. I gave it the commit message of update
gave it the commit message of update source readme and then I'm just going to
source readme and then I'm just going to sync the changes. And now inside of here
sync the changes. And now inside of here I'm going to click refresh for GitHub.
I'm going to click refresh for GitHub. And we have this now to where it shows
And we have this now to where it shows hey there's our feature dashboards.
hey there's our feature dashboards. There's our first dashboard. We can view
There's our first dashboard. We can view it on PowerBI service. Oh, I want to
it on PowerBI service. Oh, I want to view the full project one details. I can
view the full project one details. I can click on it and it navigates me to this
click on it and it navigates me to this page here where I can now see all of
page here where I can now see all of this.
Now that we got that out of the way for the restructuring, let's actually get
the restructuring, let's actually get into building out our readme for V2 or
into building out our readme for V2 or the most recent one that we just built.
the most recent one that we just built. So, I'm going to create a new folder,
So, I'm going to create a new folder, call it data jobs v2. Inside of here,
call it data jobs v2. Inside of here, I'm going to add a readme cuz we want a
I'm going to add a readme cuz we want a readme for this one. And then the last
readme for this one. And then the last thing we do is need to wherever you save
thing we do is need to wherever you save data jobs dashboard your 2.0, you need
data jobs dashboard your 2.0, you need to just go ahead and drag it in. But
to just go ahead and drag it in. But apparently that doesn't work. So
apparently that doesn't work. So navigate where it is in file explorer
navigate where it is in file explorer and then open v2. Then I'm going to go
and then open v2. Then I'm going to go ahead and just copy this and then paste
ahead and just copy this and then paste it right into here using crl +v. Now for
it right into here using crl +v. Now for the readme for project 2, we're going to
the readme for project 2, we're going to follow a very similar structure to that
follow a very similar structure to that of v1. So I'm going to just go ahead and
of v1. So I'm going to just go ahead and copy this bad boy. then go into here and
copy this bad boy. then go into here and paste it in. ControlV and so I don't get
paste it in. ControlV and so I don't get confused, I'm g close out of the other
confused, I'm g close out of the other one. Gonna minimize the explorer so I
one. Gonna minimize the explorer so I can see better and then open this view.
can see better and then open this view. All right, so this is data jobs
All right, so this is data jobs dashboard and it is V2. We need to get
dashboard and it is V2. We need to get first and update an image. For this,
first and update an image. For this, we're just going to use that snipp tool
we're just going to use that snipp tool like we learned to use previously, which
like we learned to use previously, which all we have to do is press Windows
all we have to do is press Windows shifts. So I'm going to snap a shot of
shifts. So I'm going to snap a shot of this bad boy. Go to markup and share.
this bad boy. Go to markup and share. And specifically, I want to save this.
And specifically, I want to save this. And I'm going to save this in our images
And I'm going to save this in our images folders. Project 2, page one. Save it.
folders. Project 2, page one. Save it. Now, inside of here, all I need to do is
Now, inside of here, all I need to do is just update that this is actually
just update that this is actually project 2_.
project 2_. Bam. It's appearing right here. I've
Bam. It's appearing right here. I've also updated my link for this that we
also updated my link for this that we created previously, which I can just
created previously, which I can just click on to verify that it is in fact
click on to verify that it is in fact working. It's up there. It's good to go.
working. It's up there. It's good to go. Next up, I'm going to update the
Next up, I'm going to update the introduction to make it more relative
introduction to make it more relative that we upgrade the last dashboard. And
that we upgrade the last dashboard. And I just highlighted this. This project
I just highlighted this. This project offers a streamlined single page uh page
offers a streamlined single page uh page interface to quickly explore crucial
interface to quickly explore crucial market trends. Now, scrolling on down to
market trends. Now, scrolling on down to the skills showcased. These skills were
the skills showcased. These skills were really dealing with the first half of
really dealing with the first half of the course, so they need to be updated
the course, so they need to be updated for the second half of the course. So,
for the second half of the course. So, I'm going to go ahead and delete them
I'm going to go ahead and delete them and start from scratch. With this one, I
and start from scratch. With this one, I focused on not only dashboard design,
focused on not only dashboard design, but how much we use Power Query, how we
but how much we use Power Query, how we use data modeling and also DAX. And then
use data modeling and also DAX. And then I did highlight again the visualizations
I did highlight again the visualizations we used of car charts, cards, tables,
we used of car charts, cards, tables, and whatnot. And then finally,
and whatnot. And then finally, highlighting those interactive features
highlighting those interactive features like slicers and button, buttons, and
like slicers and button, buttons, and books. For this bottom portion, we don't
books. For this bottom portion, we don't have uh two pages. So, I'm actually
have uh two pages. So, I'm actually going to get rid of all this portion
going to get rid of all this portion regarding the second portion. I'll
regarding the second portion. I'll update our image right here to be from
update our image right here to be from project 2. And I don't really need this
project 2. And I don't really need this title as well. And we're going to get
title as well. And we're going to get rid of this text as well. So above the
rid of this text as well. So above the image, I want to call out that this is
image, I want to call out that this is the second iteration of this
the second iteration of this consolidating the dashboard into a
consolidating the dashboard into a single focus page. And then underneath
single focus page. And then underneath this, I call out how we've basically
this, I call out how we've basically made this more concise and we focus it
made this more concise and we focus it on key KPIs like job count, skills per
on key KPIs like job count, skills per job, median, yearly, hourly, salaries.
job, median, yearly, hourly, salaries. Um, the last thing to wrap up is the
Um, the last thing to wrap up is the conclusion. And for this, I just
conclusion. And for this, I just highlight once again that this is a V2
highlight once again that this is a V2 and that the purpose of this was really
and that the purpose of this was really streamline a lot of the analytics and
streamline a lot of the analytics and stuff that we did in V1 in order to show
stuff that we did in V1 in order to show what is most important to job seekers,
what is most important to job seekers, job transitioners, and job swappers. All
job transitioners, and job swappers. All right, this is looking good. I'm going
right, this is looking good. I'm going to go ahead and save this. The last
to go ahead and save this. The last thing that we need to do is now just
thing that we need to do is now just update that read me on the main page.
update that read me on the main page. So, I'm going to close out of these that
So, I'm going to close out of these that way it doesn't look as confusing. the
way it doesn't look as confusing. the read me on the main page. And for this,
read me on the main page. And for this, we need to add in that V2 down here,
we need to add in that V2 down here, right? So, we have V1 for our first
right? So, we have V1 for our first dashboard. We need to highlight V2
dashboard. We need to highlight V2 underneath this. So, I've put a title in
underneath this. So, I've put a title in here for this one for data jobs
here for this one for data jobs dashboard V2. And the first thing I want
dashboard V2. And the first thing I want to do is actually show an image. So, I
to do is actually show an image. So, I start by finding that alt text and then
start by finding that alt text and then in parenthesis, the actual hyperlink. I
in parenthesis, the actual hyperlink. I also like above want to have it to where
also like above want to have it to where it goes to the PowerBI service. So I'll
it goes to the PowerBI service. So I'll put in a hyperlink to the PowerBI
put in a hyperlink to the PowerBI service. Now we're going to do a similar
service. Now we're going to do a similar format to what we did up here in that
format to what we did up here in that we're going to talk about the key skills
we're going to talk about the key skills utilized. So underneath this we're going
utilized. So underneath this we're going to be putting that and with this feel
to be putting that and with this feel free to have just chat GPT summarize
free to have just chat GPT summarize what we wrote last in order to capture
what we wrote last in order to capture those key areas we want to talk about.
those key areas we want to talk about. And then underneath this remember we
And then underneath this remember we want them to go to that read me that we
want them to go to that read me that we just created for project 2. So, I'm
just created for project 2. So, I'm going to go ahead and put a link in here
going to go ahead and put a link in here where they can v uh view the full
where they can v uh view the full project. Anytime you create any link,
project. Anytime you create any link, you should always verify that it works
you should always verify that it works and it directs me right to it. Good to
and it directs me right to it. Good to go. Now, at the bottom, here's a little
go. Now, at the bottom, here's a little optional area that I'd recommend adding
optional area that I'd recommend adding for this front page of here. And that's
for this front page of here. And that's a about section about this portfolio.
a about section about this portfolio. And this just explains that every
And this just explains that every project heads read me that you can get
project heads read me that you can get even more insights about it. And then
even more insights about it. And then they direct you to the different PowerBI
they direct you to the different PowerBI files. Okay, this is good to go. Just do
files. Okay, this is good to go. Just do a once over for this. I'm liking it.
a once over for this. I'm liking it. Let's actually get this onto GitHub. So,
Let's actually get this onto GitHub. So, I'm going make a message of project 2
I'm going make a message of project 2 complete. Do commit and then from there
complete. Do commit and then from there sync the changes. Navigating back to the
sync the changes. Navigating back to the source folder. Let's see if it's
source folder. Let's see if it's working. Okay, looks like we have our V2
working. Okay, looks like we have our V2 in there. We have our main page showing
in there. We have our main page showing our first project and then the second
our first project and then the second project as well. And make sure that the
project as well. And make sure that the links are working. And I can navigate to
links are working. And I can navigate to the project 2 readme which has all the
the project 2 readme which has all the different information in here for it.
different information in here for it. It's looking really good.
So no work ever happened unless shared on LinkedIn. We're going to go through
on LinkedIn. We're going to go through the same steps that we did for project
the same steps that we did for project one to share it. The first thing is
one to share it. The first thing is adding a project. Here under our project
adding a project. Here under our project section, we're going to click add. So I
section, we're going to click add. So I added this name of data job skill
added this name of data job skill dashboard 2. I put in these skills which
dashboard 2. I put in these skills which are different from our last one, right?
are different from our last one, right? We have PowerBI but also now DAX Power
We have PowerBI but also now DAX Power Query data modeling and add this one of
Query data modeling and add this one of KPI dashboards. For the link for this, I
KPI dashboards. For the link for this, I would direct them to the readme of V2.
would direct them to the readme of V2. And so I' copy this one here. And then
And so I' copy this one here. And then under add media, I'm going to add in a
under add media, I'm going to add in a link. Paste in that value and then click
link. Paste in that value and then click apply. One quick note, if I navigate
apply. One quick note, if I navigate back to that source folder, right, this
back to that source folder, right, this is where we linked for project one to go
is where we linked for project one to go to, which it may be okay, but if you're
to, which it may be okay, but if you're a perfectionist, feel free to change
a perfectionist, feel free to change that to this area right here for them to
that to this area right here for them to actually navigate into and see project
actually navigate into and see project one. After this, put in a start and end
one. After this, put in a start and end date. And you can go ahead and save
date. And you can go ahead and save this. Now, for those that supported the
this. Now, for those that supported the course, as soon as you complete the end
course, as soon as you complete the end of course survey, I'll automatically
of course survey, I'll automatically send you a certificate of completion.
send you a certificate of completion. And you know what we got to do with this
And you know what we got to do with this bad boy? We also got to get this onto
bad boy? We also got to get this onto LinkedIn. On your profile, under
LinkedIn. On your profile, under licenses and certifications, I'm going
licenses and certifications, I'm going to go ahead and click add. For the name,
to go ahead and click add. For the name, we'll put in PowerBI for data analytics.
we'll put in PowerBI for data analytics. List me as the issuing organization.
List me as the issuing organization. Update the issue date. There is no
Update the issue date. There is no expiration date with this, so you can
expiration date with this, so you can leave that blank. The credential ID is
leave that blank. The credential ID is located on the certificate itself and
located on the certificate itself and then you'll also get emailed with this
then you'll also get emailed with this the actual URL to the certificate so you
the actual URL to the certificate so you can actually display it that you can use
can actually display it that you can use the as the credential URL update those
the as the credential URL update those skills. I just listed the same ones that
skills. I just listed the same ones that we covered in the project too because I
we covered in the project too because I feel like those were more robust and
feel like those were more robust and then from there you can add any media
then from there you can add any media images or whatnot. I would just
images or whatnot. I would just recommend using that GitHub profile,
recommend using that GitHub profile, specifically the main PowerBI dashboard
specifically the main PowerBI dashboard here that allows them to navigate to all
here that allows them to navigate to all the different files we did for this. So,
the different files we did for this. So, I'm just going to copy this and then add
I'm just going to copy this and then add in this link here. Looking good. All
in this link here. Looking good. All right. All we got to do now, click save.
right. All we got to do now, click save. Last thing we got to do is actually post
Last thing we got to do is actually post about it because it's great that you
about it because it's great that you updated your profile, but you actually
updated your profile, but you actually need to let others know what you did in
need to let others know what you did in it. Just make it simple. I've put an
it. Just make it simple. I've put an intro of, hey, I just completed this
intro of, hey, I just completed this course. gave a quick insight of what we
course. gave a quick insight of what we built and the skills we use for this.
built and the skills we use for this. Feel free to tag myself and also Kelly
Feel free to tag myself and also Kelly in this. We love seeing what you
in this. We love seeing what you actually build with this. And then
actually build with this. And then finally, at the end, you can list the
finally, at the end, you can list the URL to the project. Also, some people
URL to the project. Also, some people just like to put it in the comment
just like to put it in the comment section because apparently it works
section because apparently it works better with LinkedIn algorithm. I
better with LinkedIn algorithm. I included a photo, too, to just make it a
included a photo, too, to just make it a little bit more engaging. And go ahead,
little bit more engaging. And go ahead, post. So, once again, congratulations
post. So, once again, congratulations for wrapping up this course. It's been
for wrapping up this course. It's been nothing short of your hard work. One
nothing short of your hard work. One last note, it's not too late for you to
last note, it's not too late for you to get that certificate of completion. All
get that certificate of completion. All you got to do is support the course and
you got to do is support the course and then complete the end of course survey.
then complete the end of course survey. Tell me how I did during this and then
Tell me how I did during this and then I'll email it right to you. All right,
I'll email it right to you. All right, if you got value out of this video,
if you got value out of this video, smash that like button. And with that,
smash that like button. And with that, I'll see you in the next one.
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