How to Become a Data Analyst: A Step-by-Step Guide

Thinking of becoming a data analyst?

You probably already know how intimidating the process of re-skilling, switching careers, and breaking into a industry that is notoriously competitive can be. Which is why it goes without saying it’s exceptionally important to embark on such a massive journey with a roadmap that supports your goals.

Without a guide, you’ll find yourself experiencing a number of problems such as poor instruction and educational material, lack of direction of what to study next, little clout with your employer prospects, and fewer responses back on your applications and resumes from recruiters.

So why, oh why, do so many would be analyst hopefuls I talk to still have a laundry list of excuses for why they can’t get started?

Maybe because, unless you enjoy going at it blind, becoming an analyst might seem daunting, time consuming, and difficult.

Well, the time for excuses is over and this guide is here to help you navigate your ways towards becoming a data analyst. I’ll cover 3 critical steps you can use as a roadmap, as well as provide helpful links to simplify your career pursuits.

Let’s get started with an important question.

What is a data analyst?

Data Analyst allow businesses and organizations to gain valuable insights and drive decision-making based on the hidden information buried within data sets. By collecting, cleaning, analyzing, interpreting, visualizing, and presenting data, they can help organizations boost traffic, brand awareness, credibility, conversions, revenue, and much more.

Today, organizations from every industry and sector are clamoring to hire skilled data professionals. They are among some of the fastest growing jobs. Don't believe me? Head over to the U.S. Bureau of Labor Statistics, and type the word 'analyst' in the search bar, and proceed to click on literally any of them. You will find that analyst job growth outlook tends to be increasing by 10-35% over the next decade, much faster than the average.

So, how do you become a quality data analyst that gets attention from employers?

What makes a good data analyst?

Before you set out to become an analyst, make sure you know the qualities and both soft/hard skills needed to succeed in fast-paced world of analytics. You may have questions like “What do I need to study?” and “In what order and how do I learn all of this stuff?”

To start, a good analyst needs a large dose of curiosity, creativity, is friendly, yet relentless. Analysts are often required to create reports and dashboards at breakneck speeds that should answer questions and help business leaders resolve a challenge they’re experiencing — and you have to do so in an interesting way.

It’s not enough just to answer someone’s questions — you must also shine light on the unknown "unknowns" while being engaging. For instance, your analysis should hook the key stakeholders and dig further into the root cause of the business issues. Together you'll discover new solutions to problems and questions they didn't know they had.

So, how do you actually go about becoming one of these engaging and insightful analyst?

1) Enroll in a Boot Camp / Get Certified

Before you start applying to jobs, make sure you have a clear understanding of data literacy and the analyst tool kit.

Build a solid foundation on the basic building blocks: statistics, data cleaning, data mining, creating data visualizations and dashboards, spreadsheets, databases, and programming.

This is where enrolling in a prestigious analytics boot camp comes in handy. Having that stamp of approval next to your name from one of the more successful names in business or education can be very valuable. Consider the extra effort involved to cross-reference and vet each source of education as a beginner with limited knowledge.

For instance, it can be difficult to cobble together a cohesive curriculum from disparate sources on your own.

You might, however, prefer to enroll in a curated boot camp or career track course that becomes a one-stop shop of information. Upon completion of the courses, you also have something to show for it: a newly minted certificate or Credly badge, with your name on it. This goes a long way showing potential employers you aren't a complete noob and are serious about continuing your own education. That kind of certified credential is what helps you prove your dedication to the skill-sets organizations really want (and need) in their data professionals.

Don’t know which data analyst boot camp is right for you? Here are a few resources to help you get started:

2) Create (a few) Projects & a Portfolio

Next, you’ll need a place to host this capstone project and every other project you author afterwards. This requires choosing a free online portfolio option available and loading it up with some projects.

Use a free online portfolio builder site.

Start using these popular sites to host your work:

LinkedIn - Professional Resume
Tableau Public - Data Visualization Portfolio
GitHub Pages - SQL or Python Programming Projects
Behance - UI/UX, Presentation, & Document Design Portfolio

While these sites won't allow you to use an original domain — they are free places to house your portfolio projects, which can be invaluable if you are cash-strapped and just starting out.

Now that you completed the capstone from the boot camp and have posted your first portfolio project to one of the sites above, it's time to cement your learning. Create a couple extra projects you are proud of to solidify your new knowledge. Having multiple pieces of work allows you the opportunity to prove to potential employers you can handle a variety of different data sets and provide insights and solutions.

But what kind of projects should you be creating?

Best project ideas for a data analyst portfolio.

Here are some ideas to get you started on what types of projects to include in your portfolio:

A business dashboard visualization project
A really intense data cleaning project (think multiple datasets, missing data that requires imputation, etc.)
Time series analysis
An A/B testing/hypothesis testing project
A geo/mapping project
Regression analysis
Some stuff that uses SQL

While these ideas aren't an exhaustive list - they should get you started. If you need more data portfolio tips, visit here. Now you may be wondering, "Where do I learn to make projects?"

Where to learn how to make data analyst projects.

Here are some great resources for helping you craft your own data portfolio:

Now that you have a shiny new certificate, and some cheat codes (projects) in hand, it's time to put yourself out there.

3) Network, Apply, but Look for 'Back Doors'

Once you have your portfolio set up, and a few custom data analysis projects, its time to start applying. However, don't do yourself a disservice by applying at your dream job right out of the gate.

For example, if you’re fresh out of boot camp, let's hold off on applying to that mega FAANG or hot new start-up for now. Temper expectations, the goal here is to basically accept the first or any analyst position you are offered. Don't pass up a company brave enough to hire and entrust a fresher like you with their valuable data. While it may not have been the dream company you envisioned, grind it out. Get your ~3 years of experience, while continuing to build your portfolio along the way. This will give you time to hone your craft. Then, when you go to apply for that dream job, you will be ready.

But how do you land that first, coveted position? Two ways to do this include:

Networking: You've been active on your social media, right? It's time to leverage it. Sometimes you have to swallow a spoonful of humble medicine and ask for help. Post you are willing to work, and could use assistance with any leads. Tap into your network, where ever you built it. And if you haven't, get started on LinkedIn.
Looking for Back Doors: Look for hidden opportunities or a round-a-bout way of getting to your goal. I had an interview at a healthcare company for an entry-level IT support agent position. During the interview process, I tossed out that I was a recent graduate of an analytics program and asked if they had a data analytics department. They hired me on as a part-time IT agent but on a path to put me in the analytics department. Over this time, I was able to get familiar with the business operations within the company, and they were able to suss me out. After about 5 months, I was moved into analytics and joined the department full time. Since then, I have been enjoying life as a data analyst.

Ready to crunch numbers?

Becoming an analyst can help you build a better quality of life through higher income potential, more flexibility when it comes to industries and sectors available to work in, and the possibly doing your work remotely. Follow the steps and tips I covered above to begin your journey of becoming a data analyst today.

If need helping landing that first job, or keep getting passed on promotion and want to create more visually stunning and beautiful dashboards in Tableau, either for your portfolio or projects at work, let's chat. I offer Tableau tutoring customized to your needs that will help you get where you want to be.

Editor’s note: This post was originally published in November 2022.

Travis Tester

Travis Tester is a healthcare data analyst and information designer based in the USA. When not analyzing or visualizing information, Travis enjoys being cozy with his wife and their three cats.