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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

πŸ”— CONNECT WITH AVERY

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Mentioned in this episode:

May Cohort of the Data Analytics Accelerator β€” Now Open

πŸ”— datacareerjumpstart.com/daa The May cohort of the Data Analytics Accelerator is officially open for enrollment. This is my comprehensive data analytics bootcamp that takes you from wherever you are to landing your first data job. Doesn't matter your background, your degree, or your experience level β€” we're going to help you get there. What you get: πŸ“Š Full curriculum covering Excel, SQL, Tableau, Python, and R πŸ› οΈ 9 real-world projects across different industries to build your portfolio πŸ’Ό LinkedIn, resume, and interview prep so you actually stand out to recruiters 🀝 Weekly office hours, coaching, and a community of 900+ aspiring analysts who are in it with you πŸŽ“ Lifetime access β€” go at your pace, come back anytime May enrollment deal: πŸ”₯ 20% off when you enroll now 🎁 6 free months of my unreleased Data Portfolio Builder tool β€” this isn't publicly available yet, and every May cohort member gets early access The live kickoff call is with yours truly on Monday, May 11th at 7:00 PM Eastern. Make sure you're enrolled before then so you don't miss it. πŸ‘‰ datacareerjumpstart.com/daa Or just click the link in the show notes down below. See you on May 11th.

https://datacareerjumpstart.com/daa

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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