How I Would Become a Data Analyst In 2025 (if I had to start over again)

here's how I would become a data analyst if I had to start all over again in 2025 now I'm lazy and I'm impatient so this method that I'm going to be choosing the SPN method is the fastest and it's the lowest amount of work to actually land a data job but it still is a lot of work Step One is I'd understand the different data roles available in the data World there are so many different data roles and it's not just data analyst there are so many other roles that are just like data analysts but

have slightly different names and slightly different responsibilities for example business intelligence analyst business intelligence engineer technical data analyst business analyst Healthcare analyst risk analyst price analysts there are so many literally so many different options that you could possibly choose from and they're all pretty similar for the most part but some things are going to be slightly different so for example a healthcare analyst you're going to be a data analyst but specializing in looking at Healthcare data financial analyst same thing you'd be looking at financial data a bi analyst like a business intelligence analyst and a

data analysts really a lot of the time are going to be doing the exact same thing so it's important to be looking for all these roles understand what these roles do and what their slight nuances are because there's a chance that your previous experience is actually valuable and would help you get a leg up in applying for these different drops so for example if you have a business degree and you're trying to transfer into business analytics becoming a business analyst makes a lot of sense or a financial analyst makes a lot of sense if you've

worked previously as a nurse or like a CNA maybe you become a healthcare analyst whatever you've done previously there's probably a good chance that that experience is valuable in the data world to a specific role so even like I have a lot of truck drivers in my boot camp those truck drivers can be Logistics analysts they can be operations analysts they can be supply chain analysts because their previous experience is actually valuable the second thing that I would do is figure out what is actually required because here's the truth there is actually thousands of data

skills and tools and programming language is out there but if you try to master all of them you're going to be like 150 before you feel prepared to start applying to jobs you're going to be dead is impossible to learn and it's impossible to master all the different data tools and skills and languages so by default have to choose a few now you have the decision to make is which ones do you choose and I like I said I am lazy and I want to do the least amount of work possible so I believe in

the loow hanging best tasting fruit analogy if you can imagine that there's a tree that has some of like a peach or an apple on it right the easiest fruit to grab is always going to be the closest so it's the lowest hanging fruit but not only do you want the lowest hanging fruit you want the tastiest fruit right so this is stuff that is not only easy to learn but is extremely useful those are the things you want to focus on out of the thousands of data skills those are the ones you'll want to

focus on you can do the research on your own if you'd like by looking at job descriptions and writing down what is actually required but that's a lot of work and you can take it from someone like me who's been in this space for about a decade now look at literally thousands of job descriptions I even have my own data job board frad job.com and I look at it all the time to see what is being required so I've done this research for you already and I will have a link to my conclusions in the

show notes down below but basically what you need to know in terms of lwh hanging fruit it's Excel Tableau and SQL that is it those are the top three skills that you should be learning as a data analyst when you're just trying to get started and if that is too hard to remember you can remember every Turtle swims right that's easy Excel Tableau and SQL that is where I'd start and I wouldn't really Veer off of that until I've landed My First Data job now you might have noticed that I didn't say Python and that

might come as a surprise to many of you because you hear so much about Python and how cool it is and how popular it is and it is really cool it can do so many different things it's so powerful and it's actually my favorite data tool but it's actually only required on 30% of data analyst roles and it's really hard to learn it takes a long time to Learn Python because python is hard but also off programming is hard and if you don't have a programming background it's going to take a long time to just

kind of even get your foot in the door in the python world and understand what's going on what's a variable what's a loop what's a function those types of things just they take time and so if you only need it for 30% of the jobs that means 70% of the jobs don't require it and once again I'm all about doing the least amount of work possible and doing it as quickly as possible so I say save python for after your first dat of job because it's really just not needed to land that first one once

again I have have a free video that kind of explains what skills you should learn and in what order and why I'll have that in the show notes down below the third thing that I would do if I was trying to become a data analyst is try to figure out how I'm going to convince a hiring manager or recruiter to hire me even though I have no prior experience there's this thing called the cycle of Doom which basically says I can't land a data job because I don't have experience because I can't land a data

job and it's this never- ending cycle of well you're never going to get a job unless you have experience you you never get experience unless you get a job it's kind of like the chicken or the egg you know what comes first so you have to figure out how am I going to beat the cycle of Doom and how am I going to convince someone that yeah I am a data analyst and you should hire me how would I do it personally I build projects projects are a great way that you can demonstrate your skills

it's basically the tangible evidence for people to know that you can do what your resume says you can do if you're unfamiliar with projects it's like almost doing pretend work where your pretending that you're working for a certain company you take a data set and you analyze it and publish your results we'll talk about where to publish them here in a second but basically it's allowing you to learn with realistic data with realistic problems but also you're creating some sort of evidence like literally physical evidence that you can show to hiring managers recruiters and be

like hey look I can do these things I can be a data analyst I can use Excel I can use SQL I can create a data visualization in tapow once I understand those three things the fourth thing that I would personally do is start with learning and I want to emphasize this is not the first thing this is not the second thing this is not the third thing it's the fourth thing that I would do is start learning and I would start learning Excel Tableau sequel every Turtle swims right and I would do that by

building projects because I think building projects is the most realistic way to learn I also think it's the funnest way to learn because just doing like pointless exercises on like these like interactive online learning things it's just not realistic like in real life you're going to be having real data sets you're not going to be in some like controlled environment you're actually going to have to be analyzing real data that's messy that has issues that has flaws and you have to figure it out and so building projects is the best way to learn because you're

also creating this tangible evidence that you're going to be able to show to hiring managers and recruiters you might be thinking well where do I get started well you need to figure out where you can buy data sets you have to have a good data set I just did an episode on this recently and I'll have the link to the show notes down below but the simple answer the one word answer is kle kaggle is the best place to find a data set it's not the only place and there's other great resources but if you're

only looking for one kaggle's usually the place I would go and i' personally build projects based off of what you want to do ultimately so go back to step one and think about it like if you have a business degree let's say you want to become a business analyst I would try to build projects that are relevant to to business analytics maybe data on sales or marketing or operations anything that's business related those are the projects I would try to seek out or if you're not sure like if you want to be a business analyst

or a healthcare analyst or maybe you don't even care you'll just take whatever you've got I would suggest doing projects on lots of different Industries maybe dip into Healthcare analytics maybe do some people and HR analytics maybe do a project on manufacturing and Engineering data that way you're getting exposed to multiple different Industries so you can kind of figure out maybe what you're interested in you're creating a robust portfolio that will be attractive to every industry and multiple companies right because if you just focus on creating you know business projects but let's say you want

to become a healthcare analyst it's like oh those projects don't really match up so that way you have a project for whatever role you might be interested in so that's particularly what I suggest doing and it's what we do inside of my boot camp the data analytics accelerator is we learn Excel SQL and Tableau by building projects and we build multiple projects in different Industries so that way we're very robust as candidates the fifth thing I would do if I was trying to become a data analyst is create a home for my projects and this

is actually what's called a portfolio you know projects are something that we do but if you just do them and you don't publish them and you don't share them they don't actually do much good you need to create a portfolio to home these projects and the portfolio platform you'll hear the most about is GitHub and I have a controversial take that I'm not a fan of it I don't think GitHub is meant to be a portfolio now that's me being a little bit picky but I just don't think it's the best option if you're choosing

from scratch what you need to do is make sure that your readmes are really good because if you have a good read me on your GitHub then it can work but if you're starting from scratch I recommend doing something like LinkedIn using the featured section or choose GitHub Pages which is from GitHub but kind of a separate product and it's their portfolio solution it's actually what GitHub recommends as a portfolio or I really like call hard c a r r d it's just a simple website builder be really great options inside the accelerator my boot

camp so any of those three would work just fine the six thing I would do is make sure that my LinkedIn and resume are up to dat and optimized and I would do this early even before I've actually mastered Excel or I've you know tackled Tableau the earlier you do this the better because your LinkedIn is your professional business card to the world and one of the really cool things is LinkedIn has a feature called open to work there's two different settings on it we can talk about it later but basically you can have open

to work for the entire world or you can just have open to work for recruiters and either way if you set up your LinkedIn correctly your LinkedIn can start to work for you and instead of you going out and applying for jobs recruiters and hiring managers are actually applying to you for specific jobs they'll reach out to you and be like hey I think you're a good fit for this job so having an optimized LinkedIn is is really key and then of course having an optimized resume is a must because once you start applying for

jobs if your resume isn't optimized you're probably not going to get many interviews and the reason is there's so many candidates trying to get into data analytics roles especially the inry level ones that recruiters and hiring managers have to use What's called the ATS which is the applicant tracking system and basically it's it's computer it's AI it's actually not even really that complicated but there's certain things you need to do on your resume to have it be optimized and ATS friendly so you can get past the computer screening and actually have a human being look

at your resume because it's so frustrating when you get rejection after rejection after rejection that you don't even know if a human's looking at your resume a lot of lot of the times you're just getting rejected by the ATS and so you need to make sure you have an optimized resume so in terms of having an optimized resume it would basically look like not having any columns on your resume or any tables on your resume and then using really keywords that match the job descriptions so that way you appear as a good applicant to the

ATS the seventh step that I would take is to start applying and I think this is obvious but a lot of people don't ever start applying for jobs and I get it because it's scary how do you know if you're ready to land a data job it's hard to know and you probably will never feel ready so I suggest just start applying anyways and when you start applying don't only apply on LinkedIn jobs LinkedIn jobs is where everyone applies and there's going to be hundreds of candidates in a matter of a few days on those

platforms the majority of the time because everyone's doing that so you might want to try something new like going to company websites or checking out my job board find a DAT job.com or some other combination of other job websites the point here is you need to be looking in multiple places and actually start applying I know it's scary but just do it Scar the next step I would do in this process is I would really try to be networking and I I would try to be networking the entire time like even in step one but

this is where I fit on today's road map is Step eight so it's way easier to get hired when you know someone in fact my brother was just recently looking for a job and having a hard time and he ended up getting an interview and Landing that job because his wife's friend worked there and like I can't tell you how often that actually happens so Network doesn't have to be hard you can do it on LinkedIn by posting and commenting on LinkedIn I think that's really important to do but I understand that's hard and a

scary step one thing that's really a lot easier is just to talk to your friends and family just say hey I'm trying to become a data analyst do you know anyone who's a data analyst does your company hire data analysts and have a conversation you're not even really asking them anything you're just opening a conversation I know this is hard and I know it's uncomfortable and I know it's not fun like it's much more fun to learn data skills than it is to network but honestly networking gets you the same if not better results than

upskilling and actually learning new data things so you can't be ignoring this couldn't be ignoring this I have to be networking no matter how hard it is now if all is going well and I'm doing all the previous eight things that I've talked about I think at this point I'd probably start to land interviews there's two parts to an interview the technical and the behavioral the technical interview is when they're going to be asking you questions about data skills it might be Excel questions or data visualization questions or oftentimes SQL questions and they'll ask you

to write certain squl queries this can be really scary and intimidating and honestly they can be really hard the cool part is they don't always occur or or if they occur they occur very easily sometimes they're very hard sometimes they're very easy it really just depends and to prepare for the Technical Resources there's a lot of things that I could do there's a lot of resources out there that would help me prepare there's something called Strat scratch that I'll have a link in the showout notes down below that you guys can check there's data lemur

there's a bunch of tools that will help you prepare for these technical interviews behavioral interview is going to be more like them trying to feel for who you are and what you've done previously and like how you would act as a human being as an employee and that is a little bit harder to prepare for because it's more of like instead of answering technical questions it's answering like personal questions there's not a whole lot of resources out there one of the things you would want to do is use the star method you want to answer

every question by saying this is the situation I was in this is the task I was given this was the action I took and this is the results that came from that action and if you answer using that method most the time you'll be good it can be scary and there's not a whole lot of resources out there for this so if you want to check out one that I made it's called interview simulator. and it basically helps you practice these questions where I'll ask you the question via video and you will respond via video

and then we'll actually grade your answer and tell you what you did well and where you could improve it's a pretty cool software I'll link to that in the show notes down below as well wow lots of links in the show notes so be sure to check those out so those are the nine steps that I would take if I had to start from scratch and land a DA job in 2025 and remember I'm lazy I'm trying to do this the easiest way possible this is what I call the SPN method you need to learn

the right skills not all the skills but the right skills you need to build projects and put them on a portfolio that's the PE part and then you need to be networking updating your Linked In and updating your resume that's the end part and it's the easiest way to land a data job now you can do all this stuff that I told you on your own and you'd be 100% okay but it's a lot more fun to do it in community and it's a lot easier to do with a coach once again I'm all about

doing it fast and easy and it's much easier to do that with a given curriculum where you don't have to be questioning am I doing this right how do I actually do this so on and so forth and so that's why I created the data analytics accelerator program which is basically a 10we boot camp to help you land your First Data job we'll go over all these nine steps Hand by hand step by step together and make sure you're ready to weigh on that data job if you want to check that out you can go

to data career jumpstart.com daa daa standing for data analytics accelerator and of course all have a link to that and the shout outs down below let me know what I missed and what questions you have I'll try to respond to everyone in the comments down below if you're watching on YouTube or on Spotify and I wish you the best of luck in 2025