How to Become a Data Analyst
Cody is a data analyst and analytics engineer with 9 years of experience. He currently works in tech on growth and marketing data analytics.
Learning how to become a data analyst can feel overwhelming.
It’s a complex topic and the internet is rife with bad advice.
When you search Google for “how to become a data analyst”, all the top articles are fluffy and non-actionable.
This guide aims to be the opposite — a concrete, comprehensive, and actionable roadmap to becoming a data analyst.
It contains everything you need to go from never writing a line of SQL in your life to landing your first job as a data analyst.
I’ll even make this bold claim:
This is the only guide you need to become a data analyst
How is that possible?
Two reasons:
1. I link to all the best resources for learning the skills you need to develop
2. I teach you how to learn
It’s common to get stuck in “analysis paralysis” wondering which SQL or Tableau course you should take.
With this guide, you won’t have to wonder.
I’ve done all that vetting for you.
And when you get stuck on something like SQL self-joins, you’ll understand how to best teach yourself this topic because you’ll have learned How To Learn.
How to use this guide
This guide is meant to be read from start to finish, in order.
There’s a lot of information that builds upon itself.
Once you’ve read it once in its entirety, come back to the sections most relevant to where you’re at on your journey.
The guide is broken up into 4 parts:
Chapter 1: Is the Data Analyst Career Right For You?
Chapter 2: How to Approach Learning Data Analytics
Chapter 3: A 6-month Roadmap to Learn the Data Analyst Skillset
Chapter 4: How to Interview and Get a Data Analyst Job
Learning to become a data analyst is not something that happens overnight.
It takes time and consistency.
Before making this commitment, you need to be honest with yourself about whether this career path is right for you.
Many of us have bad habits when it comes to learning that we inherited from the education system we grew up in.
I show you how to break these habits and approach learning in a way that will help you learn as fast as possible.
You’ll learn about data and spreadsheets.
You’ll learn your first coding language, SQL.
And you’ll learn a BI tool of your choosing (Tableau or Power BI).
All while building a portfolio of 7 projects you can leverage when applying for jobs.
If you follow this diligently, you'll acquire the necessary skills to be a viable candidate for a data analyst position in ~3-9 months.
Naturally, some people will learn faster than others.
But on average, you can expect this journey to take 6 months.
You’ll learn how to craft a resume and cover letter that lands interviews.
You’ll learn how to best apply for jobs.
And you’ll learn how to prepare for interviews.
Remember, this journey isn't just about consuming information - it's about application.
Once you read this guide once all the way through, go through each part, section by section applying what you learn.
When there’s a resource linked, make sure you go through it.
When you’re learning a new technical skill, don’t skip the guided tutorial or portfolio projects.
The information you need is all here.
But it’s up to you to use it.
Who am I to teach you this?
Hello friend — I’m Cody 👋
At this point, you might be wondering why should you listen to me.
Here are some of my qualifications:
I’ve been a Data Analyst and Analytics Engineer for a decade and have:
And now I work at a large tech company (Cash App) on the Growth Analytics side of the organization.
I’ve taught many people SQL and data analysis over the years and have interviewed and hired data analysts for my team.
For most of my life, I’ve also been obsessed with how to learn most effectively.
Using this experience, my goal is to make your learning experience as enjoyable and frictionless as possible.
So with that out of the way, let’s get started!
What is a Data Analyst?
It’s someone who analyzes data… right?
Yes and No.
Analyzing data is part of the process, but the desired outcome and the reason businesses hire data analysts is: to reduce uncertainty in decision-making.
Every business decision has some degree of uncertainty (i.e. risk) to it.
Data analysis helps reduce that risk by adding context to a decision.
For example, let’s say you own a barber shop and are trying to determine if you should raise prices from $50 to $60.
With no data, it’s a shot in the dark.
Maybe you should. Maybe you shouldn’t. You don’t really know.
But what if you went out and collected all the pricing and review data for competing barbers shops in your area?
You could analyze that data and see how your barber shop's reputation (by looking at reviews) and pricing (by looking at prices) stack up against your competition.
Say you determine that your barber shop is one of the highest-reviewed and one of the lowest-priced.
Wouldn’t you feel more confident increasing prices?
Definitely.
But there’s still risk involved.
Maybe your barber shop is so popular and highly reviewed because of your low prices and if you increase prices, you may upset your regular customers.
So you decide to talk to 10 of them and ask how they’d feel about a $10 price increase (i.e. collecting survey data).
9/10 say they wouldn’t have a problem with it.
You just used data to reduce uncertainty in the decision even more.
Going through this process is the job of a data analyst.
Notice how through each insight, uncertainty and risk are reduced.
But it is never eliminated.
Even with the most comprehensive analysis, there will still be some degree of uncertainty.
So a data analyst uses data and critical thinking to reduce uncertainty while being aware that it cannot be eliminated.
Another ancillary benefit of data analysis is that it supports business creativity.
It can be the spark that leads to new product lines, ways of doing things, etc. that you wouldn’t have thought of without strong analytics giving insight into the truth of what is occurring.
The Different Types of Data Analysts
There are LOTS of different types of data analysts depending on the industry you’re in, the type of company you're at, and the department you support.
- Product Analyst: A data analyst role typically at a tech company or tech startup that analyzes product-related data (e.g. how many users use our app every day, what product features are most popular, etc.)
- FP&A / Financial Analyst: A data analyst that works on financial planning and analysis (e.g. forecasting revenue and expenses, modeling various financial scenarios. etc.)
- Marketing Analyst: A data analyst that works with marketing data (e.g. what marketing channels provide the highest ROI, how do we make our ads more effective, etc.)
- Data Analyst: There are many roles where the data analyst works across departments providing support on the highest priority items. One day they could be building a sales dashboard for the sales team and another working on a dashboard that helps the customer success department track their core KPIs.
When you’re learning data analysis, don’t decide on the type of analyst job you want… yet.
It’s best to explore lots of different datasets and business problems.
When I got my first data analytics internship, I thought I wanted to do Supply Chain analytics.
During the internship, I spent 2 weeks at each of the 5 departments at the company (i.e. Finance, Marketing, Supply Chain, Risk, and Inventory) and did one analysis project in each.
After the internship, I realized I liked Marketing and Risk much more than Supply Chain.
Experience helps you learn what you enjoy and what you don’t.
Another reason to explore different business areas when you’re first learning is to develop business acumen (i.e. learning how businesses work).
If you only learn Marketing, you’re not going to understand how businesses operate financially.
And if you only learn Finance, you’re not going to understand how businesses acquire customers.
Strong business acumen is crucial for Data Analysts and the only way to develop it is through experience.
Lastly, when you solve lots of different types of problems in different business areas, you’ll develop a broader tool belt of solutions you’re comfortable applying.
And the more ways you have to solve a problem, the better you get at solving problems in general.
The most important thing is to train your mind to think analytically.
When you are a strong analytical thinker, you can apply those skills to whatever domain you choose.
There’s a great book called Range that talks about how many of the novel solutions to the world's hardest problems come from people who take their experience in one discipline and apply it to another.
When you dedicate yourself to one field and one discipline, you, unfortunately, develop blinders.
It becomes hard to see different approaches to problems, other than the ones you and everyone else in your discipline are comfortable with.
If you don’t get the opportunity I had in my internship, don’t worry, you can recreate this experience yourself.
To learn to become a Data Analyst, you’ll be creating data analysis projects that you’ll be showcasing in a portfolio to help you land a job.
Portfolio projects are a fantastic way for you to test out different datasets and problems from different business areas so you get all the benefits of a diverse array of experience before specializing (more on this later).
A “Day in the Life” of a Data Analyst
t’s easy to romanticize being a data analyst when you’re not one.
But since you don’t know what the day-to-day of the job is yet, it may or may not be for you.
I recommend watching a few “Day in the Life of a Data Analyst” videos.
- Shashank Kalanithi’s Day in the Life Video
- Nakya Sherrell’s Day in the Life Video
- Mo’s Day in the Life Video
People Who Tend to Excel in this Career
Anyone with enough determination and grit can become a data analyst.
But not everyone will like the job.
I know a LOT of data analysts.
They have a range of personalities and come from all walks of life.
- Logical and analytical in how they approach life
- A long attention span for solving problems (i.e. they generally like puzzles)
- Curiosity and hunger for learning
- Enjoy hearing stats and looking at charts and graphs
- Typically don’t hate (and even enjoy) math
- Detail-oriented
- Often majored in Economics, Math, Statistics, Finance, Computer Science, Physics, or another science-related major. However, I’ve also seen English, Psychology, Education, and pretty much every other degree become data analysts and love their job.
Salary and Career Progression
One of the big draws for people transitioning into data analytics is the salary.
To be as transparent as possible, here's my salary progression as a data analyst over 9 years:
Here’s a look at the average salary for a Data Analyst.
The best paying jobs are in tech ($150k-$250k), and if you go into leadership, you can make upwards of $300k-400k.
But remember, that's the top 1% of jobs, not the average.
People Who Tend to Excel in this Career
The barrier to entry is much higher for these 3 roles.
If you have no data experience, your best bet is to start as a Data Analyst and then transition into one of the above 3 once you’ve developed the skills and experience.
You’ll use nearly all your Data Analyst skillset in the 3 roles above but will have to learn additional skills depending on the role.
FAQs About Becoming a Data Analyst
Can You Learn to Become a Data Analyst on Your Own?
Short answer: Yes.
If you’re alive right now reading this, you’re incredibly lucky.
You have the internet.
Unlimited knowledge and resources at your fingertips.
Anyone, from anywhere, can learn anything as long as they have an internet connection.
Take Elon Musk, the founder of SpaceX and Tesla.
He taught himself rocket science simply by reading books, using online resources, and talking to industry experts.
His relentless self-education helped him revolutionize space technology.
I’m no Elon Musk, but was able to teach myself Search Engine Optimization (SEO).
It was a journey filled with challenges.
But with just an internet connection, I was able to learn something fairly technical without any prior education.
Still don’t believe me 😉?
Here are some other inspiring stories of self-taught Data Analysts:
Do You Need a Degree?
Short answer: No, but it helps.
Many entry-level data analyst jobs require a degree, but there are ways around this.
You’ll have to work harder without a degree and have a strong portfolio, but it’s still possible to break into the field.
One of the best strategies for landing a Data Analyst job without a degree is to transition internally.
You get a job at a company, get good at that job, and then in your spare time, start trying to take on more analytics-related work.
What Degree Should You Get?
Should You Get a Masters Degree?
Sometimes a Master's in Math, Statistics, Data Analytics, or Computer Science can help you land that first job.
My personal opinion is that a Master’s degree is only worth it if you don’t go into debt to get it.
You can easily teach yourself the same skills you’ll get from a Master’s degree using the internet for free or with affordable online courses/programs.
I recommend going that route first.
Why?
If you go into a mountain of debt, you’re forcing yourself into a career that may not end up being fulfilling to you.
When I graduated with a BS in Economics and a BS in Supply Chain Management, I had $100k worth of student loans.
I got lucky and stumbled into analytics, something I love and that pays well so I was quickly able to pay that debt off.
For many others, they aren’t so lucky.
So be careful borrowing money for something you aren’t sure about yet.
If money isn’t an issue, a Master’s degree can significantly help you land that first job by getting your foot in the door.
Check out this site and this site if you’re considering a Master’s degree.
Are Online Certifications Worth It?
Short answer: Yes, for some people.
If you’re a new grad, you don’t need an additional certification.
To be fair, a certification CAN improve the strength of your resume when you apply for internships and jobs.
They can also help you become more “job ready.”
But here’s the thing… Certifications are NOT the most effective way to learn data analysis.
They’ll slow you down.
The most effective learning technique is “just-in-time learning” meaning you learn only what you need to know just in time to apply it.
With certifications, you’ll be learning lots of things you won’t immediately apply, so it won’t all stick.
But sometimes certifications are a necessary evil.
If you’re looking to make a career change into data analytics, then I do recommend obtaining the following certifications:
1. The Google Data Analytics Certification
2. Tableau Certification OR PowerBI Certification (pick one)
We’ll talk more about these specific certifications later on in the guide.
For now, all you need to know is that these are the only certifications worth the time or money.
Do You Need to Pay Money to Learn?
Short answer: No.
Everything you need to learn data analysis is accessible online.
Some paid resources can speed up your learning journey, but don’t let money be an excuse for not getting started.
You can learn entirely for free if you’re determined.
Certifications will also cost you a couple hundred dollars so if you’re planning on getting certified, keep that in mind.
FAQs About The Data Analyst Skillset
Do You Need to Code?
Short answer: Yes.
As a Data Analyst, you’re going to need to learn SQL, which is coding.
But you don’t need to become a Software Engineer.
Think of a Data Analyst more like a “hacker”, or someone that “hacks” together scripts to get a desired output, but that doesn’t bother with the more tedious and complicated aspects of software engineering like unit testing, deploying code to production environments, etc.
Before I learn SQL, I thought coding was for super geniuses and that I’d never be good at it.
When I learned SQL at my data analytics internship, everything changed.
I got hired after the 10-week internship and then after about 6 months of working full-time, I started loving it.
I realized it’s not as complicated as it first seemed.
Since then, I’ve learned Python as well as a bit of Javascript.
Learning SQL takes time, but anyone with enough grit and determination can become great at it.
Do You Need To Learn Python or R?
Short answer: No.
You don’t need Python or R to land your first job.
And you won’t use either language in most Data Analyst roles.
I recommend ignoring Python and R until you have your first job AND feel comfortable with spreadsheets, SQL, and at least one BI tool.
If you want to learn Python or R afterward, go for it.
It’ll only make you a better data analyst.
Do You Need to be Good at Math?
Short answer: No, but it helps.
There’s a lot of math you use on the job, but it’s not advanced math.
It’s arithmetic and basic statistics.
Again, you don’t need to be a math super genius to become a data analyst.
You just have to be willing to learn the basics.
If you don’t have an extensive math education, there’s a whole section later on in the guide that’ll point you toward resources you can use to learn the basics.
Skills You’ll Need to Develop to Become a Data Analyst
Ignore advice on the internet that says you also need to learn how to scrape web data, use command line tools, or anything like that.
If you focus on these 6 skills, you’ll be in great shape to land your first job as a data analyst.
How Else to Determine if this is the Career For You?
The road to becoming a data analyst takes time.
Before committing to that journey, do everything you can to make sure it’s right for you.
Talk to already employed Data Analysts.
You can find these people on LinkedIn.
Look for Data Analysts that post regularly on LinkedIn and ask them questions in the comments sections of their posts — they’ll be more likely to respond to you over a DM.
Also, read the /r/dataanalysis subreddit.
It’s full of great information and insightful posts from people in the field.
That's it for Chapter 1!
In the next chapter, you'll learn how to learn.
Next Chapter:
How to Approach Learning Data Analytics
Cody has worked in data for 9 years as a data analyst and analytics engineer focusing mainly on growth and marketing analytics.
He has a wide breadth of experience ranging from working on a 40 person analytics team to being the first analyst at a startup to build the analytics function.
He’s also a data entrepreneur and has built and sold 2 companies in the marketing data space. Currently, he works in tech on growth analytics and GTM strategy.
Cody lives in a log cabin in the woods an hour from the nearest grocery store thanks to Space X’s Starlink internet.
