0:02 here's what I do as a data analyst I
0:05 have over 10 years experience as a data
0:07 analyst manager of data analytics and
0:10 now as a business intelligence engineer
0:13 and after all these experiences I want
0:15 to give you a realistic picture of what
0:18 a data analyst does so let's get started
0:20 the first is what is a data analyst a
0:22 data analyst is just someone that
0:26 gathers data studies it and then makes a
0:27 decision so think about when you're
0:30 buying a car you're going to want to
0:32 compare prices look at the different
0:35 features decide whether it makes sense
0:38 to lease a car versus buy it and after
0:41 all that analysis you'll then go ahead
0:44 and buy the car that's best for you so
0:46 that's basically what a data analyst
0:49 does they're going to assess all the
0:51 data points and then make a decision
0:53 based off of it and there's many
0:55 different types of data analyst I know
0:58 it's very confusing there's business
1:01 analysts there's finan financial analyst
1:03 Healthcare analyst they all
1:06 fundamentally do the same data analysis
1:09 but the biggest difference will be their
1:12 domain so a financial analyst will be
1:15 working on financial reports whereas a
1:17 business analyst is going to be working
1:20 closer with the business and business
1:22 decisions and also some of the roles
1:25 will be more technical than the other so
1:28 what do I do as a data analyst my role
1:32 is a mix of of business analyst data
1:35 engineer and data analyst like a
1:37 business analyst I work really closely
1:40 with the business to determine what are
1:43 the metrics that impact the business and
1:46 like a data engineer I then work on
1:48 ingesting the data building the various
1:50 data pipelines and then like a data
1:53 analyst I'll then analyze the data and
1:55 presented so you can already tell
1:58 there's a lot of overlap between all of
2:00 these data roles when you you say data
2:03 analyst versus data engineer versus data
2:06 scientist and if you want a video
2:08 specifically on what the differences
2:10 between all of these let me know in the
2:12 comments and I'd be happy to do it what
2:15 is the workflow of a data analyst a data
2:18 analyst works on the problem then the
2:21 data and then reporting starting with
2:23 the problem the problem statement is
2:26 like a blueprint for a data analyst it
2:28 really tells them what direction they
2:31 need to go in as as well as what is it
2:33 that they need to solve for so with the
2:36 problem statement of what is the best
2:39 car to buy versus what is the most
2:41 affordable car to buy you would be
2:44 looking at two different data sets
2:47 because the problem of what is the best
2:49 car to buy would require looking at
2:52 safety ratings versus the most
2:54 affordable car you would solely be
2:56 looking at prices and in a workplace
2:58 setting you're going to have
2:59 stakeholders which are basically
3:01 basically just people in your
3:04 organization who will have business
3:07 problems and want you to solve them with
3:09 data and I document all of that down in
3:13 a design document outlining the problem
3:15 what the solution will be including the
3:18 impact and then I include the metrics
3:19 that we're going to use in the solution
3:21 as well and make sure that we are all
3:24 aligned before I work on the data data
3:26 is not always readily available and
3:28 you'll find that in the real world you
3:31 spend a lot of the time looking for data
3:33 now once you find it you then have to
3:36 figure out how to ingest it on a regular
3:38 basis and then you work on the actual
3:40 analysis part of the data once the data
3:42 is prepared then you'll do the
3:45 presentation part which is reporting
3:47 it'll either be through a visualization
3:50 in a bi tool sometimes it's a simple
3:53 Excel report other times it's a data
3:55 solution in this process you want to
3:57 make sure that you're using your
3:59 communication skills getting feed
4:02 feedback and also documenting everything
4:03 so that if someone asked you a few
4:05 months later what this report was you
4:07 have everything documented what does a
4:10 data analyst team look like well it can
4:13 either be a team of one or a team of 10
4:16 there really is no standard here you may
4:18 find a role where you're the only data
4:21 analyst and I've been there but I didn't
4:23 really like it because I felt that I
4:26 didn't have anyone to bounce ideas off
4:29 with and no one to learn from whereas
4:33 now I'm on a team of data Engineers as
4:35 well as partner software engineers and
4:38 just being surrounded by a team helps me
4:41 learn a lot so I prefer having a larger
4:43 team and if you're debating and you even
4:44 have a chance to decide I would
4:47 recommend going with a bigger team what
4:49 is the realistic life of a data analyst
4:51 I feel like the data analyst life has
4:54 really been glamorized on social media
4:56 it's the trend of people working from
4:59 home making six figures working in Tech
5:02 it's really good but there are just some
5:04 realistic downsides that you should be
5:07 aware of such as working with
5:10 stakeholders who will have unrealistic
5:13 expectations of work from you at the end
5:16 of the day I get a ping from someone who
5:18 says hey can you work on this report and
5:21 get it done by end of day and I'm
5:24 thinking it already is end of day then
5:26 it puts you in a spot of having to work
5:28 late and then when you ask those
5:30 clarifying questions of hey what exactly
5:33 is it that you need they don't even know
5:35 and being honest there actually have
5:37 been times where I've had to log in at
5:41 900 p.m. even because last minute I get
5:43 a request saying hey can you pull this
5:46 report and so having to manage the
5:49 unrealistic idea that you can pull
5:52 reports quickly and deliver it happens a
5:54 lot and you should just be aware of how
5:56 to manage your stakeholders and it's not
5:59 only last minute deliverables but you'll
6:01 get a lot of side chats from people
6:04 pinging you all day they'll have
6:07 questions like hey why isn't this
6:10 dashboard working or hey can you look
6:12 into this one problem I have honestly
6:16 responding to all those reports take up
6:19 your whole day and before you know it by
6:21 5:00 you got nothing done knowing all
6:24 this why am I a data analyst well there
6:26 are two reasons the first is work life
6:28 balance so that part is true I have to
6:31 say as a DayDay analyst I do have a lot
6:33 of time to myself and I think that's
6:36 really important because previously I
6:38 was working as a consultant working
6:41 50-hour weeks and by the time you're
6:43 done with work and commute honestly I
6:45 had no time to myself and that's what
6:48 made me realize that it's important to
6:51 have a good career but also equally
6:53 important to have a good life outside of
6:56 your career and so being a data analyst
6:58 does allow me to confidently make plans
7:02 with my friends friends at 5:00 or have
7:05 enough time to work on my side passions
7:07 like YouTube and if you are enjoying
7:10 this video please like And subscribe as
7:12 it helps me a lot and just having the
7:15 ability to have time to myself is really
7:18 the deal breaker for me and second is
7:22 the pay so a data analyst pay is very
7:24 competitive I'll be honest especially
7:27 working in Tech the salary is closer to
7:30 150,000 250 ,000 and if you're
7:32 interested more in the salary and want a
7:34 whole video on that let me know in the
7:36 comments because I can do that as well
7:39 so should you be a data analyst honestly
7:41 anyone can be a data analyst and
7:44 learning technical skills is something
7:47 that anyone can do but what I feel like
7:49 is overlooked a lot is people don't talk
7:53 about the soft skills that also are
7:55 really important in addition to the
7:58 technical skills and yes the technical
8:02 skills will get you your first job and
8:04 put your foot in the door but once
8:07 you're there I think what I learned from
8:10 all my experience is that those soft
8:12 skills of being able to communicate
8:15 influence others make connections with
8:17 other teams is really what will get you
8:21 promoted will get you a better job those
8:24 are skills that I think are equally as
8:26 important and so if you're thinking
8:29 about a data analyst career think about
8:31 all the things I said and see if that is
8:34 something you realistically see yourself
8:37 doing still want to be a data analyst
8:39 watch my next video on how I'd become a
8:42 data analyst if I had to start over
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