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So you want to be an Analytics Engineer | Microsoft Reactor | YouTubeToText
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Summary
Core Theme
This session, "So You Want to Be an Analytics Engineer," from Fabric Data Days, aims to demystify the role of an Analytics Engineer, particularly within the Microsoft Fabric ecosystem, and provide guidance on acquiring the necessary skills and career paths.
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Hey everyone, thanks for joining us for
the next session of Fabric Data Days. My
name is Anna. I'll be your producer for
this session. I'm an event planner for
Reactor joining you from Renmond, Washington.
Washington.
Before we start, I do have some quick housekeeping.
housekeeping.
Please take a moment to read our code of conduct.
conduct.
We seek to provide a respectful
environment for both our audience and
presenters. While we absolutely
encourage engagement in the chat, we ask
that you please be mindful of your
commentary, remain professional and on topic.
topic.
Keep an eye on that chat. We'll be
dropping helpful links and checking for
questions for our moderators to answer live.
live.
Our session is being recorded. It will
be available to view on demand right
here on the Reactor channel.
With that, I'd love to turn it over to
our presenters for today. Thank you both
>> Hello everyone.
>> Hello everyone.
>> Welcome. Welcome to So You Want to Be an
Analytics Engineer. We will jump right
in. Thank you so much Anna for that
introduction in the code of conduct. Uh
and we will start with Shabnam with an introduction.
introduction.
>> Thank you Stephanie. Hello everyone. I'm
Shabnam Watson. I'm a Microsoft data
platform MVP and I help companies with
their data and AI projects. I've worked
with Microsoft data products for 20
years and for the most recent years I've
been focused on PowerBI and then most
most recently on Microsoft Fabric.
Speaking on uh speaking about Microsoft
Fabric and PowerBI, I'm also
co-authoring a book on analytics
engineering with Microsoft Fabric and
PowerBI which is a great timing and I'm
so happy to be here today in this
session uh talking to you about it with
Stephanie of course. So Stephanie back
to you.
>> Thank you so much Shabnam. I'm so happy
to be here with you today. Uh my name is
Stephanie Bruno. I'm also a data
platform MVP and a Microsoft certified
trainer. I am an independent consultant
and trainer for mainly fabric and
PowerBI. Um like Shabnam, I've got about
20 years of experience in this field and
have been mainly focusing on fabric and
PowerBI in the past few years. Um and I
am joining you today from Pittsburgh,
Pennsylvania where it's very very cold.
Um so next up, let's meet our
moderators. We are so lucky to have
three experts today who are going to be
very happy to answer all of your
questions about fabric in the chat.
We've got Anu Pama, Philippa, and Chris.
So feel free to make this very
interactive. Ask them all of your
burning technical questions and they'll
be happy to answer them for you.
So with that, let's learn a little bit
more about what we're all here for.
We're here for Fabric Data Days, which
is 50 days of live learning,
certification prep, vouchers. I know a
lot of you are probably here for the
vouchers, uh data viz contests,
community connection, and more. So,
there's a lot to be uh part of with this
fabric data days. So, just make sure you
you look at this link here, this aka.ms/fabric
aka.ms/fabric
data days. The organizers will put lots
of links in the chat for you throughout
the hour together. Uh but when in doubt,
visit aka.msfabricdata
days for all of the information. Um so
we'll start with just what we can
expect. We've got a fabric data days.
This is a little bit of the schedule. So
earlier today there was a get certified
um from Azure data engineer to fabric
data engineer. And what we've got now is
so you want to be an analytics engineer.
Uh, next up tomorrow is going to be
leveling up your analytic skills with
the DP600. So that's very relevant to
what we're talking about today. We'll
just touch on that a little bit today,
but you're you can learn a lot more
about that tomorrow. And you can see the
rest of the upcoming um events on this
schedule, but this is just a little bit
of the schedule. There's even more. So
make sure you go to these links below um
to see more detail on what you can experience.
experience.
We've also got contests and challenges.
Um, this is a great way to both get
practice and get involved with the
community. It's a good resource for
learning and for inspiration. So, you
can see, for example, there's a contest
on data viz, there's a contest for
students, there's a contest for
notebooks. Um, so it's really a great
way to even if you don't want to enter
anything into the contests, um, it's
it's a great source to just at least
check out, you know, you can learn a lot
from these contests and challenges.
>> Did you run the data viz um challenge or
the world championship in Fabcon? The
last FabCon.
>> The last FabCon. Yes. In Vienna. Um,
right. So there was the uh data viz
world champs which was really really
exciting to be part of. It was amazing
to see what people could build. Um my my
mind was blown with that one. Um and I
know there's a lot of that going on too.
So you can actually see some of the
interviews with the people that were the
finalists in that. So highly encourage
you to see that. Um and also just one
note, you know, these contests are a
great way to get involved in the
community. Um Shabnam and I have known
each other now I don't even know how
many years, five years or more. um
because we bumped into each other at an
event and you know it's a great way to um
um
>> I was gonna say what you're into 20
maybe [laughter]
>> it wasn't past summit actually we met
through the community we met at past
comm um SQL conference in Seattle a long
time ago.
>> Yeah. Yeah. It's great. So, I love being
part of this community because I get to
meet and learn from uh people like Shopnam.
Shopnam.
>> So, definitely jump into these contests
and challenges.
>> We also have um some certification
challenges and here you go for these
links for your discount vouchers. Um so,
there are skills challenges with the
learn modules. You can also check out if
you have a local user group because a
lot of them are hosting study groups for
the DP600 and the DP700.
Um, and so just again, you know, join
your community. If there's a local one,
you're in luck, but there's a lot of
virtual communities, too. Um, so you can
definitely participate in that. Um, you
can get these discount vouchers for the
DP700 and 600. Those are 100% discount.
and the PL300 and DP900 have a 50%
discount. So again, we've got these
great links here. These should all be in
the chat for you. So you can This is how
you can go and you can learn more about
what you need to do uh to snag yourself
one of these vouchers.
And if I went through that too quickly,
here's this great big QR code that you
can grab. So you can we'll leave this on
the screen for just a second. Um, this
is a great opportunity to be able to get
yourself certified for free. So, these
certifications can be really helpful for
a lot of reasons. Um, such as, you know,
it just looks good on your resume,
right? It's a way to show off that you
know what you're doing. Um, it also for
me, I like it because it makes me learn
parts of fabric that maybe I haven't had
the opportunity to work on in my
day-to-day job. So, it's also a great
learning uh experience and especially
for free, right?
>> Yeah. Chabnam, did you have any I think
you had a whole great laundry list of
good reasons to get certified. I'm going
to put you on the spot.
>> The ones that you said, I think mostly
it's a great uh way to learn the
product. It gives you some, you know,
incentives to,
you know, finish it at a certain time,
especially if you're going to take
advantage of the uh free vouchers to
take the exam. It's always good to give
yourself a timeline to work on something
and then the certification itself really
is really helpful to give you a good
idea of the product end to end and like
Stephanie said you may not be using some
parts of it in your day-to-day life even
if you're using it. So this helps fill
those gaps for you. So in that way was
super helpful for me when I took either
one of the exams.
>> I totally agree. Um, and another way to
learn uh are these free instructor-led
handson workshops. So there is fabric
analyst in a day. You can see this link
here, next FIAD and real time
intelligence in a day. And here's just a
quick plug. You'll have a lot of these
opportunities coming up. Many are
virtual. And on January 13 specifically,
Shabnam and I are going to be delivering
one together. Um, so we do have a link
uh tinyurl.com fiadjan13.
fiadjan13.
So hopefully that's getting in the chat.
Um, but if you want to join Chabnam and
myself for an all day free uh fabric
analyst in a day, you can register there
or you can do it sooner if you want to.
>> Okay. So what are we here for? We are
here because you want to be an analytics
engineer. So this is the specific
content for today, right? Um we're going
to learn a lot about um the different
roles. You know, you don't have to come
from a specific background to be able to
do this, right? So you can come to this
from many many different career paths.
No two journeys look alike. So we're
going to learn all about how you can
take the skills that you already have
and use those and propel yourself into
an analytics engineer. We will also give
some practical guidance on how you can
build this experience and get these
skills. So this, you know, the goal
isn't to give you this single road map.
There is no one path to do this. Um
we're just going to learn about all of
us and where we've come from and how
we've landed here today. And we're going
to show you that it doesn't matter what
your background is. Um you can gain
these skills, this knowledge, uh this
community, and you can be an analytics
engineer as well.
So specifically what we're going to
cover is what even is this? What is an
analytics engineer? And it's really
funny because Shopnam and I have had a
long conversations about this. It's not
super clear, right? Um it's fuzzy.
There's overlap with other roles as
well. So we'll talk about that. We're
going to talk about the skills that
matter to become a fab uh an analytics
engineer specifically working in fabric
for this. uh how you can get started if
you're new at this and what are some
career paths and some next steps that
you can do uh to get there. So, we're
going to go through all of this and by
the end you should have a clear
understanding of what an analytics
engineer is and why the role is so
important in the fabric era and then how
you can start building toward it.
So, just a reminder, you know, this for
those of us who are here right now
together um live, you can ask your
questions in the chat and you have a
bunch of people that are experts in this
field and they can answer your questions
for you. Um so, let's just get started
by getting to know each other a little
bit. And if you don't mind, let us know
in the chat what your current role is
because we're going to see that we're
coming from this from all different
paths. Um, so we would love to just hear
a little bit more about um who you are
and where you're coming from.
>> And so we can talk about that a little
bit in the in the comments. And with
that then I'm going to turn it over to
Shabnam to talk about what this
analytics wonder what is and I'm trying
to do the same thing that the character
is doing. What is what is an analytics
engineer? Um so it's one of the terms
that has guess become popular in recent
years. Um I think so many of us may have
been doing this type of job before it
was called an analytics engineer. Um so
what the literature says what it is is
that it's someone who bridges the gap
between the super technical folks that
bring in data from outside resources and
then uh gets that data models it and
makes it reusable and understandable by
business people so that they can create
reports from it. So by definition, it's
a role that sits between the technical
folks at a company and the business
folks. So that's the um easiest
definition that I can give. And now if
that sounds vague, it's because it is
vague. So let's dig in and talk about it
and see what that is.
Um so in recent years or probably now
more than recent recent years so I would
say for a decade uh the data teams have
been evolving but in organizations but
there's still these silos that needs to
be broken down. So there's still lots of
lots of silos in the companies um
regardless of what everybody wants the
landscape to be. So business on one side
needs to have clean data, reliable data
and then on the other side um you need
to have somebody who's technical enough
to be able to work with whoever is
bringing the data in and then take it
and makes it make it presentable um in a
form that includes the business rules
and it can grow with the company and
then give that to the report developers
or the analysts. So the role of the
analytics engineer itself has been
evolving over the last decade or so. So
when I think about an analytics engineer
for example from myself I've been really
working in this role in recent years
because I've been working with projects
that are really big projects. So they
have dedicated
data transformation teams that they
bring data from their sources and they
land it somewhere and then they have
dedicated analysts that work with
business to create certain reports.
where I've been sitting is I've been
sitting in the data modeling space
creating those semantic models and then
creating the star schemas and
translating the business requirements
that the analyst give me into metrics
that are reusable. Um so with that if
you want to look at the landscape of
roles in the data uh in the data
ecosystem these are some of the key
roles. Now this doesn't include every
single role that's out there. So for
example the architect role is missing
from here. There's always a data
architecture that oversees the whole
process. Hopefully that role isn't here.
Um but as you can see it's sitting
between the source data and the business
people. It's a it's a person who
collaborates across many different
teams. So it needs to be a technical
person and also somewhat businesss savvy.
savvy.
So um with that said now what does an
analytics engineer do if you want to dig
in a little bit more. So what are the
core responsibilities?
Uh it's the modeling the data. So
building clean, reliable uh tables and
relationships. Again, this doesn't mean
it's the person who's doing the data
ingestion. Uh that would be a different
role. That would be a data engineer. Um
but it's the person who starts from the
point where the data engineer has
finished their job and then continues
from there. turning data, messy source
data that's raw in its form and then
taking it through maybe the uh medallion
layers and promoting it and then
creating reusable models and metrics for
everybody else to use.
>> Just to add on to that, you know, I kind
of feel like it also depends on your
organization where you are. You know, if
you're in a smaller organization, you
might be the the data engineer, the
analytics engineer and the data analyst
and the visual design, you know, you
might be all of those. And I also think
that in in different organizations,
there's some overlap, you know, between
the data engineer and the analytics
engineer. Um, so it's not this hard and
fast line. It's really a little bit
squishier than that. And you'll find
that different organizations will have
the different roles um have more or less overlap.
overlap.
>> Yes. Um
so uh I see Shannon saying it's a data
um
Yes. So and also that's correct. So
anybody who's we're and we're going to
talk about that in a little bit. So for
those who are working from PowerBI in
PowerBI space, fabric is the natural
progression to take their skills and
then take it to the enterprise level. So
we'll talk about that in a little bit.
Um so as far as the skills, so what are
the skills that some we expect the data
uh an analytics engineer to have? um the
the way that Microsoft has created um
these roles and corresponding
certifications, it has been by doing a
lot of research with Microsoft partners,
with customers
um and organizations to see how
Microsoft can create these
certifications that really apply to
those roles skills so that they're
relevant. So you take this
certification, it's actually going to
help you become a better data analyst or
analytics engineer or data engineer. And
so what you see here is that we have
three exams that are relevant to this
space. A PL300 is mostly PowerBI is for
data analyst and then from there when
you want to grow into the analytics
engineer that's when you take DP600 and
of course there is also DP700 and DP700
is for the data engineers that there
those are the ones who are going to do
the uh some of data ingestion and work
with pispark that the analytics
engineers mostly do not. So,
So,
>> I think also with the the PowerBI, the PL300,
PL300,
um, I was looking at the skills measured
for that one and I feel like you could
get away with pretty much spending most
of your time in PowerBI desktop. Um,
other than the admin piece of that, you
know, you could learn what you need to
do for the PL300 mainly in desktop, not
fully, but mainly, whereas the DP600,
you can't. You definitely need to be
within fabric for that. What do you
think about that kind of differentiator?
>> That that's actually exactly what I was
going to say in the next slide. So you
you made my life easier. [laughter]
>> Sorry about that.
>> No, that's perfect. So when you actually
look at the DP600, when you look at the
categories, okay, so one of the first
categories is maintaining a data
analytics solution. So what does what
does that mean? That means um thinking
about the things that you just said.
It's about um adding governance and
monitoring and security and things that
you do in the service versus in PowerBI
desktop. So all those workspace rules
and things [clears throat] like that
they're they're all in the maintain a
data analytics solution. So that's the
natural progression to go to DP600 from PL300.
PL300.
Whereas some of the third category which
is implementing and managing semantic
models the implementing part of it
specifically that part is going to have
an overlap with uh PL300 because those
are the things that you can do in
PowerBI desktop as far as creating
creating a model relationships cardality
calculations things like that.
Um so
>> why do IQL on why do I see KQL on this
list Jnam?
>> Um so it's at the bottom. Great
question. It's at the bottom and the
list of languages that you need to know.
Uh so KQL
um I think in the so for for everybody.
So KQL um originally was not in this
certification. So if you took this
certification a long time ago, you did
not have KQL. You instead had Pispark.
Um since then pispark has moved to DP700
but uh has been replaced with KQL. So in
here KQL is would be in um I would say
preparing data.
Um I think it falls under the preparing
data. So, um,
these these are just very high level
categories. And so, if you want to learn
more about DP600,
the exact skills that go into each
category, the best place to start is
Microsoft learn. And what you want to do
is you want to go to Microsoft learn and
then type in DP600 study guide. That
study guide is your guide that you need
for the whole um to prepare for the exam
and know exactly what to read, what's
included and it will keep you on track.
So um I think KQL is in the preparing
data because you would be uh querying
quering data with it. Does that make sense?
sense?
>> That's not something that's going to be
on the PL300, right? Because you're not really
really
>> correct so much in desktop for example.
>> Yes. PL300 does not have as far as I
know it doesn't have SQL doesn't have
SQL and doesn't have obviously KQL
um it's purely PowerBI
>> right and I think that's an important
distinction because yes as the analytics
engineer um SQL is really important you
need to be able to query your data
wherever it is um yes
>> not just pull it in with power query right
right
>> yep SQL SQL continues to be I call it
the king of analytics and I think it
will stay it will stay for a long time I
hope um although I have to say my second
favorite language is KQL because of its
simplicity and its power it's um almost
for me it rival SQL okay
okay
so um so all right so how do you build
your analytics engineer skills. And like
Stephanie said earlier, there's no one
right way to do things or to learn this
stuff. So, we're curious to know for all
of you who are live with us right now,
uh what's your favorite learning method?
Like, how do you learn? Like Stephanie,
how what's your favorite learning
method? Do you like watching training
videos or do you read? What? How do you learn?
learn?
>> No, it's funny cuz I'll read or I'll
watch a video and I'll think, "Oh, yeah,
I get it." But if I then try to do it, I
won't. You know, it's like I have to get
my hands into it. So, having an actual
lab to go through and click and
understand and make mistakes and come
back, that's really the best way for me
to learn. How about you?
Yeah, I think for me uh watching the
training videos um they help me a lot
and then I will go and read a little bit
about it and then obviously trying
things will solidify the learning in my
in my head. So it's a combination of um
it's a combination of them. And also I
noticed that um the method that you
learn may also shift throughout your
career. So just because you were really
good at learning by reading, it may not
be the same when you advance in your
career. So I would say explore all
different options and see which one
works for you. Um, and definitely uh
when it comes for when it comes to
passing the certifications, you do want
to have some hands-on experience. Even
if it's within the, you know, a trial
capacity or a lab environment, I highly
recommend you have some hands-on uh
practice because the purpose of the
certifications is not just for you to
pass the test and put it on your resume
that you pass the certification.
hopefully it's for you to actually learn
some of the material.
>> Yeah. And those hands-on activities that
are so important for my learning. I
really appreciate that. Um on Microsoft
Learn, there are a lot of those where
you can, you know, you can jump in and
there are these lab environments. It's
not everywhere, but it's in a lot of it.
And that helps me a lot. Um just because
it's so funny how much I think I know
something and then if I try it, I'm
like, "Wait, what was that? Where was I
supposed to click? What does this mean?
So, I need to I need to just get in
there and and break things to learn it.
>> Yeah, it it always looks easy when
someone else is doing stuff and um you
know, you're like, "Oh, that's not that
hard. I can do it." And then when I try
it, it's really hard. But yeah, so
repetition uh makes things easier. >> Okay.
>> Okay.
>> If only I would have learned that a long
time ago.
Yeah. So, um, all right. So, let's talk
about working in Microsoft Fabric. Um,
when it comes to an analytics engineer
and preparing for DB600.
Um, so just a quick recap of Microsoft
Fabric. Microsoft Fabric is an
end-to-end analytics and AI platform in
in uh a software as a service format
meaning that it's um backed by Microsoft
cloud and you don't install anything you
don't configure any uh services. Uh so
for example if you're coming from an
Azure background you're maybe used to
Azure data bricks or Azure SQL DB this
is entirely different so this is very
close to what PowerBI
is and actually it has inherited
PowerBI's foundation as far as the uh
workspace model the capacity model and
the security. So you have all of these
tools in the cloud that you can do uh
data projects data and AI projects with.
So you have data factory which is the
green icon here to do ETL or ELT in the
cloud. Um and then you have the blue
icon which is called analytics here.
That's the uh data warehouse, data
lakehouse. That's where data engineering
goes. That's where you have access to
these massively parallel processing uh
engines um that you can use for your
analytics. This is where you get your
lakehouse and warehouse. And then uh we
have now we have also the purple icon um
databases which supports the OLTP
workflows. So the analytics workloads
are for what's called OLAP workflows.
Those are workloads that are for
analytics. So these are queries like
they they're really good at answering
queries like uh give me the sales by
store for the last 10 years u by region.
So those are analytics queries compared
to OLTP workloads where they're read and
write heavy applications, transactional
systems like point of sale systems or
customer relationship management
systems. So now we have the OOLTP
support with the arrival of databases
also in fabric.
The next workload in fabric is real time
intelligence. This is for handling
streaming data. So instead of landing
the data and then promoting it through
layers and as it goes through layers you
apply transformations.
This is for cases where you're working
with data in real time in near real time
uh at high volumes and it's streaming
and you want to apply transformations on
the fly as it's arriving. So it's a
really powerful component of Microsoft
fabric. And then we have PowerBI which
is for creating semantic models and
analytic analytics and reporting. Um I
think PowerBI just turned 10 years so
hopefully most of you have used PowerBI.
Um and then the last two icons that you
see there for industry solutions and
partner workloads. So these are uh
pre-built solutions either by Microsoft
or third parties that are available in
Microsoft uh fabrics portal. when you go
to the portal. Um, so Stephanie, I think
that was a uh Did I miss anything? Do
you want to add anything?
>> Um, just that you know fabric uses the
open standards like parquet, delta,
spark, tsql, python. So it's not like
you're just learning fabric when you're
learning these skills. Uh these skills
do transfer to other platforms as well.
>> That that is absolutely true. So when I
was actually taking the I was learning
uh pispark for DP600 before it left it
before I left that exam the pispark that
I was uh learning I was also using it at
work a uh in data bricks in the
notebooks so um because a lot of the
along the same lines because the
foundation of Microsoft fabric which we
don't have on this slide is one lake and
Everything in one lake is in an
open-source data format called Delta
Paret. That means that all of these
engines can write to it and all of these
engines can read from it. But not only
that, you also are not locked into
Microsoft. So hopefully you will stay
with Microsoft, but you're not vendor
locked. You can now have a lot of other
tools interact with your data. So your
data stays in the same place and it's an
opensource format. So all the other
engines who can understand delta perk
can also talk to it which is a huge
benefit over previous systems where once
you put your data for example in SQL
server on prem SQL server onrem was the
only tool who could understand it.
So uh great reminder to talk about one
lake. Um, all right. So now for the DP600,
DP600,
you will be tested on certain components
of Microsoft Fabric. So by the way,
Microsoft Fabric, as you can see, has
huge capabilities. Nobody can be expert
in all of these um areas. Um, and if
you're just getting started, uh, don't
let all of the icons overwhelm you. You
can to do a project you can be choosing
just PowerBI and data factory for
example and the databases uh or couple
other components. You don't have to know
all of the tools and use all of them. Um
so for DP600
you will be tested on data factory with
the pipelines and data flows. From the
analytics uh category you will be tested
with uh SQL. So with the with the
warehouse you need to know SQL with the
SQL analytics endpoint of the lakehouse
you need to know things you can do with
SQL and then uh with real time
intelligence is the KQL component of it
that in DP600 you need to be able to um
write C uh KQL queries. By the way the
the queries that you write when I say
write queries in the exam you don't have
to write from scratch. are always a drop
down or a drag and drop kind of um
question. Uh and then PowerBI. So you
need to know DAX for DP600. So for those
of you who are coming from PowerBI
background, uh you should find this exam
easier to take because you already know DAX
DAX
>> the data factory component because you
already know Power Query. So
>> exactly you know you're really just a
data flow gen 2 is is Power Query. So
that's part of what you're going to have
in data factory. So if you are coming
from that PowerBI background, it it is a
little less overwhelming.
>> Yes, that's true. Um so and we when
you're um this this uh session is not
about preparing for the exam, but I just
want to throw this out there that
because there is there are three
different categories and three different
languages. So the in the exam so if you
know SQL and DAX then maybe you can uh
study KQL less or rely on KQL less but
if or if you know SQL and KQL really
well then you may want to not study DAX
um like in depth for the purpose of
passing the exam. So it's really nice
that there's three different languages
in there and you can focus on two out of
three for passing the exam.
So, uh, Stephanie, what what are your
favorite languages out of the three?
>> You have been singing the praises of KQL
for a long time. I know you're a
convert. Um, >> yes.
>> yes.
>> I don't know a lot of people that would
say Dax is their favorite, and I am also
not one of them. [laughter] I have a
lovehate relationship with Dax.
>> Yeah, I like for for the I like Kill.
The reason I say KQL is also
specifically for the for the exam like
if you if you are new to DAX and KQL and
you want to learn one to pass the exam I
would say 100% KQL because KQL is
straightforward. So if you look up the
syntax you can answer the question
whereas with DAX there's the whole you
know context and all that stuff that
makes it complex. So all right
>> I'm with you.
>> Yeah. So, all right. So, now I think
we're going to go back to you,
Stephanie, and you're going to tell us,
all right, how do we get started? How do
we get started to gain some of these skills?
skills?
>> I think it's excellent. So, let's talk
about how we can get started. So, we
just talked about what is the engineer.
So, hopefully we all have a rough idea.
You know, again, it's a little bit
squishy, uh, but we know what the
analytics engineer roughly is and we
know what are some skills that are
required. So, what can we do? I think
I've actually seen a lot of questions in
the chat about okay so I get it but but
now what can I do um so you know it's
about taking small practical steps so we
need to access the core tools we don't
have to get everything at once but we do
need the core tools a good idea is to
maybe pick a small project you know work
through it end to end even if it's just
with sample data and then really instead
of focusing on the specific tools you
want to focus on understanding the
workflow so from collecting and cleaning
data to modeling it. Um, it's that
mindset that transfers across platforms.
So, you know, you think about using
tutorials, sample projects. And again,
community resources. I'm just going to
um make a plug for that one more time.
The community is just the best place to
learn. So, the key is not mastering
everything immediately. It's uh
experimenting, making mistakes, you
know, figuring things out, problem
solving, and learning the process. So,
first up, I would say start with
Microsoft Learn. Um, I think we, you
know, we mentioned it a little bit. Uh,
there are a lot of tutorials and
learning modules, and some of them even
have kind of like a lab environment, so
you can actually get hands-on with it.
So, you can complete these relevant
these paths. Again, focus on a workflow
because this is what you're going to
need to understand in this role. Um,
it's not just about the specific, you
know, button clicks. It's about
understanding how how am I going to get
the data? What do I have to do to
transform it? How should I be modeling
this for what my end users need to see?
Um, so start with Microsoft Learn. These
these learning paths are just fantastic.
They help a lot. Um, so pick a pick a
few that match. You know, you don't
necessarily have to do every everything
in the order that's presented to you. So
pick a few that match what you're trying
to learn. So if you're uh interested in
the analytics engineering, look for data
preparation, modeling, PowerBI. So do
the exercises. You want to learn by
doing in a guided way.
Next up, how can you get handson in
fabric? Um so ideally you're going to
have an environment. Maybe you can have
a you can set up a trial where you can
start building. Um, so you're going to,
um, set up that trial account. Account's
the wrong word, but you'll set up a
fabric trial, jump in there, and just
start building things. Um, but some
people may not have that ability, right?
Maybe your work isn't allowing you to
set up a trial. Maybe you don't have a
work account. Um, so again, you can
attend one of these fabric analyst in a
day trainings. So it is completely free.
Um, many, many of them are virtual. the
one that Shabnam and I are doing again
on January 13 and you can see the link
on here I think um this is virtual and
it does give you an environment so it
gives you a virtual machine that you can
just get into and start building so you
don't actually have to have uh fabric on
your own. You don't have to have an
account to be able to to use this. So
this is a great way if you don't have
access um to actually get in there and
get hands-on
>> and and some people take more than one
of them. So you can you can take the
same one a few times. That way you you
will get access to the environment a few
times and get some hands-on practice.
>> Yeah, that's a good point. Um we always
like having people in there. We always
uh like helping people learn. Um so
don't be shy. Feel free to join one. And
there's also the real time in a day. So
uh feel free to join one, both, whatever
works for you. Okay. So now let's say
you've gotten in, you do have you have
access, you can work on something,
right? You've got an environment. Um so
maybe the first thing is just pick a
project, right? Um so start small
because the idea is that you want to
understand the flow. Um so you'll you'll
have a data source or multiple data
sources. Um it's not going to be exactly
how you need it to consume in PowerBI.
So this is where your transformation's
going to come in. Um maybe you're going
to build some shortcuts. Maybe you're
going to do some data flows and then you
might even decide that you want to do
some notebooks with some PI pispark even
though that's not necessarily part of
the DP600 exam. Um I was surprised to
find out how much I love notebooks and
pispark you know coming from SQL and
DAX. Now I love notebooks in Pispark
just because I started building things
with it and I thought it was really
cool. Um so this is what you want to do.
You want to find what you're interested
in. Um, if you have a project at work,
you know, have something build a build a
project that's similar to what you need
to do at work or if there's just
something you want to learn. Um, there
are so many opportunities. There's so
much sample data. There are all of these
challenges and contests that you can
participate in, for example. Um, so just
choose something and and get your hands
in there. you want to have hands-on
practice because the more you experiment
and make mistakes um the faster you'll
internalize this workflow and you'll
develop these skills that you can use in
So let's say you've gotten in there and
you know you've had some frustrations,
you're trying to figure something out um
and you just can't figure out the
answer. So this is where these community
resources can come in. So there are
tutorials, blogs, sample files, forums.
Um you can join the Reddit community. I
know that's very active for example and
again uh you know doing these contests.
Um there's also you know it's more
PowerBI but there's workout Wednesday
for example. You can look up workout
Wednesday and you can do some PowerBI
challenges. Um, so anything that you're
interested in doing, there's likely a
community person who has uh built a
tutorial or a blog or there might even
be a challenge out there. So, just to
highlight a few of these, um, here are
some names of people that have lots of
great content specifically on the DP600,
for example, or on this role. Um, so if
you want to just look up some of these
people on here, you'll see that they
have loads of fantastic content. Um and
you see Shabnam's name here. She's got
some great content on um some of these
some exam prep for example and like she
mentioned earlier in the intro um she's
got a book on analytics engineering. So
I think we can get that link in the chat
as well. Um what is the what is the
official title of your book Shabnam?
>> It's it's uh called analytics
engineering with uh Microsoft fabric and
powerbi. Um, so
>> was that with Nicola?
>> With Nicola Ilick. Yes. So it's not it's
not um finished yet. It's in early
release. So the way it works is that if
you're um you have if you have access to
O'Reilly platform, they let you read
books as the authors are writing it. And
the idea is that because the technology
advances so fast, it lets you have
access to uh the material sooner than later.
later.
Um, and you know, fabric evolves with
such a fast pace. So, it's always a
challenge with the with the book also,
um, because we have to make changes as
we go. But anyways, it's it's an early
release, so it's not published yet. Um,
but I appreciate the shout out there.
Um, I also in the in the community that
you have um, members that you have
listed there. I just wanted to um
mention the Alexi partinan and I was
trying to put a link to his YouTube
channel. I think Pam has has I can add
it in there. U he has a lot of training
videos for um the certifications as well
and Microsoft Fabric uh great content there.
there.
>> Yes. Fantastic. So again, just a real
shout out to all of these community
members who have created so much content
to help us all um both learn and prepare
for these certification exams. So all
right, so you've built some things.
You've uh solved some problems. You've
had some challenges. You got your
community resources. So now that you've
done a few projects and you've leveraged
your community resources, it's time to
iterate and reflect because this is
where real growth happens. Um it's not
linear, right? It's definitely cyclical.
So, you'll start simple. You'll get some
feedback and you know what happens to me
a lot. I'll be walking my dog and I'll
realize a different way I could solve
the problem, you know, and I'll be so
excited to get back to my computer and
jump back in. Um, so, you know, document
what works and what doesn't. You will
have some lessons learned and this is
the reflection that's going to help you
replicate your successes and avoid
repeated mistakes and it will help you
build your confidence. So the goal is
not to master everything at once. You're
just trying to have continuous learning
through practice. And over time, this
will allow you to build this solid
foundation that will transfer across
tools and will prepare you for the real
work um of being an analytics engineer.
So let's talk about some career paths
and some next steps. Um again, there's
no single path. Everyone's journey looks
different. So, um I think I saw someone
in the chat saying they work in a dental
practice, for example. You know, we come
from all kinds of backgrounds. I spent
many, many years in nonprofit. Um so, we
don't all have the same start, right?
So, all you really need is, you know,
curiosity and you want to solve
problems. And if you find this work at
all fun, then I think you're going to be
successful. Um, like for me, I just love
it when I can solve a problem and make
something work and make it faster. Um,
that's that's what, you know, keeps me
doing this all the time. So, it doesn't
matter what your background is. Um, if
you just get involved and you do these
challenges and you learn and you get the
skills, um, you're you're going to be
fine on this path as well. So, let's
talk about some different paths. None of
none of our careers look the same. um we
can start from analysis, engineering,
business roles, you know, it doesn't
really matter. And our early experiences
don't lock us in. They just
[clears throat] give us more experience
and knowledge um and just a different
background that we can provide for other
people. So try these different projects,
these different rules uh roles and tools
and you know see what resonates with you
and what fits your interests, your
strengths and where you're hoping to go.
and focus on building skills, not the
title that you hold. I mean, I'm sure if
we we could probably all have some
laughs in the chat about, you know, what
our titles are versus what our jobs
really are, right? So, focus on what you
can do and the skills that you want to
learn because employers care more about
what you can do than what the title is.
So if you have skills like data
modeling, visualization, analytics
workflows, these are transferable across
roles. So you'll want to build your
portfolio through projects, contests,
contributions again because these are
concrete experiences that speak louder
So finally, what are some different
things you can do? you can seek
mentorship, learn from others experiences,
experiences,
um or even just more community members.
Just get involved, you know, attend some
events if you can, if they're in your
area, and get yourself out there and
talk to people. Um if you have a local
user group, definitely go to that.
Everybody is there on generally a
volunteer basis. They're there because
they want to help people. So, it's a
great way to meet people and learn from
people that really do want to help you.
Um, if you don't have a local user
group, that's okay, too, because there
are all of these online communities um
where people also want to help you. So,
just remember, take small steps. Um,
just try to build a project, learn new
skills, um, allow yourself to make
mistakes and learn from them and um, and
tackle some challenges.
>> It's always um, I love the local user
groups because, um, they just give me
energy. I just get a lot of energy from
going to these local user group events.
Sometimes it's really hard to drag
yourself to a user group meeting in the
evening or you know on on weekends like
on a Saturday to go join some of these
free one-day events that they have. But
you but it's always been worth it for me
because I'm always like, "Oh, why am I
why am I doing this to myself? I'm so
tired. Do I really, you know, sometimes
I'm like, can I even learn anything when
it's this late in the day and I'm tired,
but then I go and I'm like, oh my gosh,
I actually learned something. Even if
it's just a little bit of something,
they it adds up over time. And then
plus, you get to meet other people who
are doing um jobs that are very similar
to you and then you talk to them, you
hear their challenges, you learn that
there is dirty data everywhere, so
you're not just alone, you know. So,
it's always good to hear um from other
people their their challenges and how
they're solving them and just to
socialize um with them. So, I love our
user groups. >> Yes.
>> Yes.
>> Yep. Absolutely.
All right. And so, I think Shabnam, it's
it's you now. Tell us more about
>> Yeah. So, I think um
we're just I'm just going to uh go
through a couple of closing slides and
then if you have a few minutes, we can
answer any questions that are out there
um in the in the question section. Um
so, all right. So, um
let's see what's what other things there
are in the fabric data day. So, we we
saw the schedule earlier. Um by the way
this one was the first of the so you
want to um something right? So this was
the first one. So hopefully you enjoyed
this one. There is bunch of others
coming in the same format that's going
to introduce you to the other roles the
other data roles. So so you want to be a
data analyst, you want to be a data
engineer. Um and as we mentioned um
there's always going to be an overlap
between these roles. Usually there's not
a clean cut there. Uh especially if
you're working on the smaller projects,
smaller organizations.
Um so make sure that you attend as many
as these as you can, especially if
you're new to the product or new to the
certification path. And then um
if you take the challenges again the
challenges are a way to motivate you to
give yourself a time to finish a task.
Um if you can take advantage of the
challenges and the discounts it's it
makes it even uh easier to go ahead and
take the certification. Um because a lot
of people sometimes uh they're afraid to
take the exam because they're afraid of
failing the exam. But at least having a
100% discount voucher hopefully should
make it easier and take some of that
fear away so that you can go ahead and
uh take the exam.
All right. And here is the QR code one
more time. And remember when you scan
this QR code there's some requirements.
So you have to mention that you watched
one of these sessions which hopefully
all of you have done this one or there's
some other requirements. I believe you
have to register for one of the um the
challenges to be able to take this uh
voucher and there is a timeline to it.
So you must commit to taking the exam by
the end of this year.
Um we also talked about the in a day um
events. I'm not going to talk about them
anymore. I think we talked about this
several times. Uh Stephanie, you did a
great job with that. And then uh finally
if all the resources for fabric in a day
event uh not fabric in a day my mind's
still there u but the 50 days of fabric
uh fabric data days um is here in this
link and I think um at this point we can
uh just stop and then um for the few
minutes that are left answer any
questions from our audience.
Um, I see a question. How can I train
slashinform non-technical stakeholders
about the benefits of PowerBI and
Microsoft Fabric? Some are change
resistant, but other departments have
seen measurable benefits. What do you
think, Shabnam? What's a good way to
show the benefits? Yeah, that's oh my
gosh, that's a really that's a really
hard one because you do want to have
sponsorship in order for the project to
be successful. So, you definitely need
to have the non-technical stakeholders
back up uh your project. Um you you um
you mentioned that other departments
have seen measurable benefits. So maybe
get those departments to demo the
benefits that they've got to your
department or you know their
their head the head of that department
maybe at a higher level they can talk to
your department and showcase what
they've done. I mean that internally
should be a really good example for your
department to follow. Uh, the other
thing you can do is maybe you can do a
PC and then show them what it's like and
things they can get. Um, maybe you can
even get them to try one of these fabric
in a day events or some of the trainings
to get them excited about it. Those
those are the ways I think about. I
mean, Stephanie, what would you do?
>> Um, I think also find some kind of
lowhanging fruit that maybe you could
build fairly quickly. a a good candidate
I've always noticed is if you can find
some manual process that some tedious
process that somebody has to do um and
maybe that can be if not fully automated
maybe semi-automated in fabric um so
maybe just a quick P that's kind of a
lowhanging fruit and then maybe include
a little wow factor too you know so like
I don't know something with co-pilot or
or the new translitical task flows that
allow you to do right back into power
into the database from PowerBI or you
know just some kind of like something to
make them gasp a little bit. [laughter]
>> Yeah, I agree. I agree.
>> Uh so let me see
our moderators if you see any questions
that we haven't answered or you have not
answered um feel free to post them
again. Um one for those who already got
a certification, what resources exist to
continue learning? I would say this is
where these challenges and contests come
in. Um you know, because they give you a
starting point and you now that you've
got the certification, you know how to
do some things.
>> I I think it'll like spark some
creativity for you. Um and then you can
share what you build through these
challenges and contests. I think that's
a great resource for continued learning
as well as learning from other people's
>> into these contests.
>> Yes. Also, if you want to learn, one of
the best ways to learn is to present. So,
So, >> true.
>> true.
>> Yes. So, prepare now that you've learned um
um
internally to your company or to your
community user group. Uh try to teach
one of those topics to someone else or a
new topic that you want to learn. That's
one of the best ways for yourself to
also grow.
>> Yeah, that's a great point. I love that.
Um, that definitely is what I did. You
know, I started speaking at local events
and it terrified me. Um, and I was
really afraid of looking stupid, right?
So, I wanted to I wanted to make sure I
knew the content inside and out. Um, so
that was a great way for [laughter] me
to learn.
>> Yes. the the although for those who are
who are thinking about starting your
local user group is the friendliest
place to start. The local user groups
support new speakers and their their
whole purpose is to for the community.
So um that that's a good place and even
if you're if you're a new speaker no
one's going to expect you to be perfect
and not make mistakes. So don't worry about
about
sounding um you know not so perfect. Yes.
Yes.
>> Yep. 100%. Yep. That those are some
great resources, good ideas.
>> Um and I don't see any others. So, I
would just say, you know, make sure you
continue to uh follow along with these
data days, come to some more events. Um
check out all of the opportunities that
are available and um we'll see you in
the next one.
>> We have one one last question. I just
want to squeeze the answer to that one
in. So someone asks about the user
group. So a good place to find your user
group is on the meetup. So um you can
search for whatever city is close to
you. Type the city and then uh PowerBI
user group or fabric user group and that
will bring up the meetups or the yes
shout out.
>> That's it. So hopefully everybody
enjoyed this session and hopefully
you're going to join the rest of the
soul you want to be and hopefully it's
clear for everyone what an analytics
>> Thank you.
Thank you all for joining and thanks
again to our speakers.
This session is part of a series. To
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link on the screen or in the chat.
We're always looking to improve our
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