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195: If I Wanted To Become a Data Analyst in 2026, This Is What I'd Do
Episode 195 β€’ 27th January 2026 β€’ Data Career Podcast: Helping You Land a Data Analyst Job FAST β€’ Avery Smith - Data Career Coach
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Here is how I would approach becoming a data analyst in 2026 if I were starting over. Focusing on the right fundamentals early changes everything.

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⌚ TIMESTAMPS

00:00 – How I’d Become a Data Analyst in 2026

02:00 – Learning the Right Skills Through Projects

04:30 – Why Certificates Don’t Matter

06:30 – How to Stand Out and Build Trust With Hiring Managers

07:32 – Creating a Portfolio and Networking to Land the Job

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Transcripts

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If I wanted to become a data analyst in 2026,

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here's exactly what I would do.

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I'd break it down into two separate parts.

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Number one is the, what do I actually

need to know to become a data analyst?

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The skills, and number two is

how do I actually stand out

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first, what do you need to learn?

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Where should you learn it?

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The biggest thing when it comes to

becoming a data analyst is actually

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knowing the tools to analyze the data.

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Not only knowing the tools, but also

having the mindset of a data analyst.

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And in my opinion, those are actually

both learned best through doing

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projects and real life examples.

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A project is basically like a use

case or an actual like real world

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example of you analyzing data.

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I'm not a really big fan of like all of

these silly online tutorials and all these

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silly like, oh yeah, like step-by-step.

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This is this little sandbox

and this is how you do this

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and this is how you do that.

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I just don't feel like

it's super realistic.

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I personally.

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Learn best by doing

hands-on real practice.

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And so I think why not

just start with that?

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I also wouldn't learn everything

because there's so many different

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things you could be learning, and my

old philosophy is we need to get your

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foot in the door as quickly as possible

so that way you can start to get paid.

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To learn on the job.

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Like if you're going to try to

learn everything before you feel

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ready to apply to data analyst jobs,

you're gonna be like 89 years old

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before you start applying for jobs.

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And, uh, I don't know about you, but

I don't wanna be working when I'm 89.

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So you first need to shrink the amount

of things that you're going to learn.

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So in my opinion, the first thing that you

should learn is excel, just 'cause it's

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really easy and it's really in demand.

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Second thing you should learn is Tableau

or Power bi, because they are also very

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in demand and pretty easy to learn.

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And the third thing you should learn

is sql, because once again, pretty

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easy to learn and pretty in demand.

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I think you should put R

and Python on the shelf.

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And honestly, anything, any other

tool really on the shelf right

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now, just start with those big

three, uh, BI tool, Excel and sql.

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Ignore everything else because it's just

gonna keep you in the study tutorial.

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Hell, for a long time.

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Not only would I be learning those

things, I would just be trying to learn

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to think as a data analyst, so when I

get a data set, you know, what does it

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actually mean to clean the data set?

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What things should I be looking for?

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Or in the data set that might

make it dirty or hard to analyze.

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Then I, based on the data set I

have, I would start to already think

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through what are the different things

that I can do with this data set.

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So, for example, if you have a date

column, you automatically know, hey, this

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is some sort of a time series data set.

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I can do some sort of a time series

analysis, like create a line chart or

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do some sort of predictive modeling

like arima to predict, you know, how

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this trend will continue down the road.

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You know, five Decembers from now.

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Like what is their numbers

actually going to look like.

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If you have categories,

you can say, okay, like.

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What was this quantitative

variable, like some sort of a

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price or some sort of a number?

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How does that number change

the different categories?

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So like if you have like a blue

product and a red product, like

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did the blue product sell more

or did the red product sell more?

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You know, what were the different

margins on each of those?

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Like those are the different

things that you can start to try

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to learn to think as an analyst.

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In my opinion, it's actually really

hard to learn to think of an analyst.

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Learning the skills is not

easy, but it's a lot easier than

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learning to think like an analyst.

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The only way I really try to teach

other people to think as an analyst

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is one, give them realistic examples

where they can actually go through

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the process step by step of like,

oh, okay, I kind of get this.

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I kind of get this.

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And the other one is what I call project

hacking, which is basically you see

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someone else's analysis and read through

what they did, and you think, oh, okay.

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And you do that enough.

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Eventually you start to think like

an analyst, like there's no magic

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bullet, there's no framework.

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I can give you right now that's

gonna help you think like an analyst.

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It just comes with experience.

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And experience is just the amount

of time that you, uh, have hands-on

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analyzing data or hands-on reading

someone else analyzing data.

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I think those are like the

only two ways that you can

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start to think like an analyst.

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Now, I'm not a big fan of

certificates because I actually

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don't have any certificates.

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Like I don't have the Google

Data Analytics certificate.

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I don't have any like Comier,

TIA certificates, I can't

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even say the name, right.

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I don't have an IBM certificate.

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I don't have a meta certificate.

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I literally have zero certificates, landed

all of my data jobs in my corporate.

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Career without a certificate.

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And I don't think certificates are really

built to teach you the best because I

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don't feel like they're very hands-on

project DI feel like they're kind of

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unrealistic, kind of handholding baby.

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Uh, and I just think people

like are like, oh, like I need a

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certificate to be a data analyst.

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No, you don't.

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You literally don't, and if you think

that having a certificate is gonna make

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a difference, I don't think it is because

it's never made a difference in my career.

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I've talked to a lot of hiring managers

and recruiters, they don't really care.

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There's no like standardized certificates

to have in data analytics field.

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So personally, I think doing hands-on

projects is infinitely better than

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doing these silly certificates.

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That actually leads me into the second

half, which is okay, let's say you learn

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Excel, you learn sql, you learn Tableau.

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Great.

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But how do you actually stand out now?

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Because the data analyst job market is

very competitive, especially kind of at

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that entry level junior data analyst role.

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Like how do you actually stand out?

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And I think there's a

couple different keys here.

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I think one of them is to

actually broaden your job search.

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Because literally you guys, everyone

is looking to become a data analyst,

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but there's like literally 20 different

titles that you could be searching

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for that aren't exactly data analysts,

but basically they're a fancy title

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to say that you're a data analyst.

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I can't list them all right here, but

business intelligence engineer, financial

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analyst, product analyst, pricing analyst,

a lot of things that have the word analyst

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in it are going to be good for you.

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Um, because a lot of the

times it's just like, hey.

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Data analyst role plus domain

smash together, get a new title.

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And a lot of people aren't

looking for those roles.

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So they're less competitive, but they're

literally the jobs you're looking for.

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Now I have proof of this because

I actually run a data job board.

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It's called Find a Data job.com.

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We post about 30 data jobs a day.

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Um, we try to include a lot of these like

kind of alternative data analyst roles.

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And I actually have all the data, all

the click data of you guys going to

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that website and what do you click on?

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And it's actually unproportional

data analyst roles.

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Like if it literally says data

analysts, those get like, I think two

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to three times more clicks than like

a financial analyst or a business

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analyst or a marketing analyst or a

pricing analyst or something like that.

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And literally, the job

description could be the same.

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It's just everyone loves the title data

analyst and that's what they're used to.

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And we just love what we're used to.

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So I would say.

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Try to apply less to like data

analyst roles and more of these like

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niche terms that basically mean data

analysts but aren't data analysts.

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The other thing you're gonna have to

figure out is like how do you convince

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the hiring manager or recruiter that

you can do what a job description says

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that, that you need to do because you

don't have prior experience, right?

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So it's like the cycle of doom, right?

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I can't get a data job because

I don't have data experience.

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Well, why can't you get data experience?

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It's like, oh, it's 'cause

I don't have a data job.

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So you're in this never ending

cycle and it's like you need

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someone to take a chance on you.

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But in order for someone to take a

chance on you, you actually need trust.

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And trust is hard to get, especially

when you don't know someone, right?

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We trust people that we know, and

you're going to be applying to

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recruiters and hiring managers

who don't even know you at all.

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They don't even know your face.

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They hardly know your name.

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They just know A PDF that you

gave them with some stuff on it.

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So that's where like.

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Really doing a good job on your

resume, really doing a good job on your

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LinkedIn, maybe trying to send cold

messages and actually networking, right?

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Like if you can get a cold message

to a recruit hiring manager that they

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actually like, that puts you so much

far against all the other competitors.

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If you can have like a friend or a

family member kind of refer you, then

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all of a sudden you're more trusted.

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'cause they probably

already trust that person.

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So like you need to come up with a

game plan to actually get trusted

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by a recruiter or a hiring manager.

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And that is hard to do, like I said.

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Updating your resume, making

it really good, making sure

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your LinkedIn is really good.

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And then the last thing I

think is creating a portfolio.

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So remember we talked about those

projects earlier, how it's the best way

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to learn, creating those projects and

then putting 'em on a online portfolio

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where it's like, Hey, this is literally

tangible evidence that I can do the

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what the job description's asking.

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Like the job description right here,

like look at here is a project.

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That I did that basically nears

what the job description is.

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And that way you're making yourself

a little bit of less of a risk.

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It's like, Hey, look, hiring

manager, you're worried about me.

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I've already done this

before and here's the proof.

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So like, go ahead and take a

look at the proof right here

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and uh, trust me I can do this.

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And creating portfolio is

very good for those use cases.

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So I think creating portfolio and

networking really come in clutch here.

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Unfortunately, I think most people

when they try to become a data analyst,

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they do one of these certificates where

they learn some skills in some sort of

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like lame tutorial, or they get like

their certificate at the end you're

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like, yay, I'm all certified now.

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Or they do something like data camp

or something like that, and I just

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think you're missing out on projects.

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I think you're missing out on portfolios.

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I think you're not spending enough time.

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Emphasizing your LinkedIn, your,

uh, resume and your networking

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and your cold messaging skills.

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'cause like those things are really

important because everyone knows

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at this point, everyone knows

how to analyze data in Excel.

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Everyone knows how to analyze data in

Tableau, like what makes you different.

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And that's really what's gonna make

you stand out is having a portfolio,

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a good LinkedIn and a good resume.

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So personally, that's kind of what I

would focus on instead of what most

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people are focusing on right now in

this:

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competitive to actually land a data job.

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If this resonated with you and you're

like, yes, I want to actually do this.

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I'm interested in creating a portfolio.

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I'm interested in only learning some

of the skills and then learning on

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the job and getting paid to learn.

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I actually run a bootcamp where I teach

people exactly how to do this from

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zero to landing their first shaded job.

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We'll create a bunch of projects together.

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We'll put 'em on a portfolio.

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We'll update your LinkedIn, we'll update

your resume, give you templates for both

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of those, and help you network in cold

message recruiters and hiring managers

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to actually land that first data job.

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If you're interested in learning

with me, you can check it out

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at data crew drums sot.com/daa,

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or you can go to the show notes

down below and click to learn more.

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