What Degree Do I Need to Become a Data Analyst?

Getting an in-demand job as a data analyst often starts with getting the right skills and qualifications. For many, this might mean a degree. In this article, we’ll discuss whether you need a degree to become a data analyst, which degree to get, and how a higher-level degree could help you advance your career.

Read more: What Does a Data Analyst Do? A Career Guide

Do I need a degree to become a data analyst?

Most entry-level data analyst jobs require a bachelor’s degree, according to the US Bureau of Labor Statistics [1]. It’s possible to develop your data analysis skills—and potentially land a job—without a degree. But earning one gives you a structured way to build skills and network with professionals in the field. You could also find more job opportunities with a degree than without one.  

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Google Data Analytics

This is your path to a career in data analytics. In this program, you’ll learn in-demand skills that will have you job-ready in less than 6 months. No degree or experience required.

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Average time: 6 month(s)

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Spreadsheet, Data Cleansing, Data Analysis, Data Visualization (DataViz), SQL, Questioning, Decision-Making, Problem Solving, Metadata, Data Collection, Data Ethics, Sample Size Determination, Data Integrity, Data Calculations, Data Aggregation, Tableau Software, Presentation, R Programming, R Markdown, Rstudio, Job portfolio, case study

Data analyst degrees: What should I major in?

Not all universities offer a bachelor’s degree in data analytics. So what should you major in if you want to pursue a career as a data analyst? Even if your university doesn’t have this specific degree, it likely offers other majors with overlapping skills.

Possible majors for data analysts

Here are some degree options that typically teach common data analysis skills. If you’re looking toward a career as a data analyst, these majors could be a good fit.

• Data science: In response to the increasing demand for data professionals, more and more schools are offering bachelor’s degrees in data science. In this degree program, you’ll typically take courses in computer science, statistics, and mathematics. Some programs let you specialize in fields like economics, finance, business, or health care.

• Computer science: The emphasis on statistical and analytical skills in many computer science programs makes them a good fit for aspiring data analysts. This degree is also widely available. Depending on the program, you might study artificial intelligence concepts, algorithm design, and programming languages that you can use in your future career.

• Applied mathematics, or statistics: Traditional mathematics degrees generally prepare learners for careers in academia. Applied mathematics and statistics degrees shift the focus to real-world applications, like helping businesses make data-driven decisions. The curriculum might include other important skills, like programming languages or statistical software packages.

• Finance/economics: If you think you might be interested in working as a financial or business analyst, consider getting your degree in finance or economics. Many of these degree programs include coursework in statistics and analysis, and some offer concentrations in business analytics. 

• Psychology: It might not seem obvious at first glance, but psychologists use data to describe, explain, and even predict human behavior all the time. A Bachelor of Science in Psychology might expose you to math and statistical analysis coursework.

• Management information systems (MIS): With this degree, you can get a behind-the-scenes look at databases and how they work. This could prove useful as a data analyst. MIS coursework typically covers topics like database design, data management, and business theory. With some programs, you can specialize in data analytics, business intelligence, or data management.

No matter what you choose to get your degree in, be sure to take classes in statistics, calculus, and linear algebra, as well as some computer science classes that cover database and statistical software. If you already have an industry in mind, it can help to take some industry-specific coursework (finance, health care, or business, for example).

Learn more about earning your bachelor’s degree online through Coursera.

Is a master’s in data analytics worth it?

While a bachelor’s degree is the most common entry-level qualification, some companies look for candidates with a master’s degree in data analytics or a related field. A 2017 study by IBM found that six percent of data analyst job descriptions required a master’s or doctoral degree [2]. That number jumps to 11 percent for analytics managers and 39 percent for data scientists and advanced analysts. 

In general, higher-level degrees tend to come with bigger salaries. In the US, employees across all occupations with a master’s degree earn a median weekly salary of $1,497 compared with $1,248 for those with a bachelor’s degree [3]. That difference translates into $12,948 more each year.

If you’re looking to advance your career in data analytics or move into data science, earning your master’s degree could set you up for success.

Read more: Going Back to School: 7 Things to Consider

Get started as a data analyst

Take the next step toward a career in data analysis, no matter where you are in your learning journey.

• Build a foundation of job-ready skills with a Professional Certificate in data analytics from industry leaders like Google, Meta, or IBM.

• Request more information about earning your data analytics degree online.

• Try a popular data analytics course to see for yourself if it’s a good fit.

professional certificate

Google Data Analytics

This is your path to a career in data analytics. In this program, you’ll learn in-demand skills that will have you job-ready in less than 6 months. No degree or experience required.

4.8

(106,013 ratings)

1,500,627 already enrolled

BEGINNER level

Learn More

Average time: 6 month(s)

Learn at your own pace

Skills you'll build:

Spreadsheet, Data Cleansing, Data Analysis, Data Visualization (DataViz), SQL, Questioning, Decision-Making, Problem Solving, Metadata, Data Collection, Data Ethics, Sample Size Determination, Data Integrity, Data Calculations, Data Aggregation, Tableau Software, Presentation, R Programming, R Markdown, Rstudio, Job portfolio, case study