Step-by-Step Plan for Becoming a Data Analyst

As of 2021, we recommend you get a bachelor’s degree in a STEM field—mathematics, statistics, computer science, engineering, or economics are all good choices.

Almost all data analyst jobs require a degree, and unlike many other careers, the learning you do in college will be relevant to your work.

A bachelor's degree also provides the educational foundation you'll need to advance your career in the data field. Jobs such as data scientist often require a master's degree.

If getting a STEM degree isn't an option but you still want to be a data analyst, don't despair.

Bootcamps provide a structured way to quickly build the skills you'll need for the job, and the best bootcamps successfully place graduates with some of the biggest tech companies in the world.

A few important notes on data analyst bootcamps:

1. It won't be easy, so be ready to work hard. Data analysis is a technical field, and if you're starting without a background in STEM, you will have to push through a steep learning curve to be successful. Be ready to hustle both inside and outside the classroom.

2. A bootcamp is just the beginning. It will help you get to a basic level of proficiency, but if you want to be successful in a data career, you'll need to keep building your skills to progress.

3. Many data analyst bootcamps advertise themselves as "data science" bootcamps. This is a reflection of their marketing, not their curriculum. Data science requires skills and knowledge that simply can't be learned in only six months if you're starting from scratch.

A "data science" bootcamp will put you in a good position to get a job as a data analyst, not as a data scientist. In order to progress to data scientist, you'll need to get great experience, build additional skills, and may need to go back to school.

Structured query language (SQL) is the programming language used to build and talk to databases.

Writing SQL queries is the #1 skill for any data analyst. It's the key that gives you access to the data you need to do every other part of your job.

Python is a programming language that's used to analyze and visualize data. It's a far more powerful and flexible tool than programs such as Excel or Tableau.

But Python isn't just for data analysis. It lets you do all kinds of other cool stuff too—like build apps, code games, and automate different tasks.

Hiring managers prefer data analysts with Python knowledge, so it will instantly put you ahead of the competition. Once you're got the job, Python will help you do it better and advance in your career faster.

Data visualization allows you to create the reports and dashboards to tell stories with your data. It's one of the most important things you can learn.

There are a variety of data visualization tools on the market, but we recommend getting started with Microsoft PowerBI.

Even if the company you end up working for uses a different analytics platform like Tableau or Google Data Studio, most of the principles are the same, so you'll be able to learn it quickly.

Despite all your fancy new toys—like Python, SQL, and PowerBI—you'll still need use spreadsheets quite a bit as a data analyst. Make sure your knowledge of Excel is advanced and rock-solid.