Guide to Master's in Data Analytics Programs

A master's degree in data analytics can prepare you for a job as a data analyst, business intelligence analyst, management consultant, or data scientist.

Fortune Business Insights projects that the global big data market will grow from about $307 billion in 2023 to over $745 billion by 2030. This rapid growth continues to create significant demand for data analysts. Whether you are already a competent data professional looking to upskill or have just graduated as a non-STEM major and are searching for a career, this degree may offer an ideal pathway.

The following guide explores what you can do with a master's in data analytics, schools that offer these programs, and how to choose the right degree for you.

Why Should You Get a Master's in Data Analytics Degree?

While no degree can guarantee a high salary, people with master's degrees earn considerably more than bachelor's degree-holders, on average.

In March 2023, for example, Indeed reported that salaries increased by 20% between a bachelor's degree and a master's degree. At the other end of the scale, unemployment rates decreased by 0.20%.

As Payscale reports, people with bachelor of science degrees in business data analysis earned an average of $72,000 a year, while people with master of science degrees in the field earned an annual average of $84,000.

Earning a degree in analytics offers more than high salaries, however. With your education, you can help solve problems for medical providers, scientific researchers, corporate executives, and government leaders.

What Can You Do With a Master's in Data Analytics?

Many industries face an ongoing shortage of talent in data analytics. Graduates can apply for positions in healthcare, finance, business analytics, and the sharing economy, among other sectors.

Despite the name, not every data analytics graduate has to work as an analyst. Depending on your skills and interests, you might prefer a career as a database administrator, business researcher, or management consultant.

The following careers are just some of your options after completing a graduate degree in data analytics.

Where Can You Get a Master's in Data Analytics Degree?

Listed alphabetically, the schools below represent institutions reporting a graduation rate greater than 50%. All the data comes from the National Center for Education Statistics (NCES).

What Can You Expect From a Data Analytics Graduate Program?

A data analytics master's degree helps prepare you for an engaging and in-demand career in data analysis, engineering, or management. Some schools offer master's degrees in the discipline, while others feature MS programs in computer science or MBAs with a concentration in data science. The best choice for you depends on many factors, primarily your career goals.

In a typical master's in data analytics, courses cover mathematics, statistics, data analysis, programming languages, and machine learning. As a graduate student, you can expect to conduct extensive research, typically concluding the program with a capstone project, professional portfolio, or master's thesis.

Most degrees require 1-2 years to complete, but some schools provide accelerated options that take less than 12 months.

Admission Requirements for Data Analytics Graduate Programs

You need a bachelor's degree to apply for graduate school, and some institutions accept senior-year applicants. Not every school requires a computer science-related major, but you should be familiar with the basics of statistics and computer science.

Many graduate programs require a minimum 3.0 GPA in the discipline, overall, or in the last 60 credits. You may also need to provide GRE or GMAT scores, depending on the school.

Popular Master's in Data Analytics Courses

Each data analytics program establishes its own curriculum, and courses may differ significantly among schools. The examples listed below represent some of the most common data analytics courses:

• Data Analytics in R: A core component of the program, this course emphasizes common statistical techniques used in data analysis. Students explore logistic regression using additional classification techniques, with all analyses conducted in R.
• Data Manipulation: Students practice loading, manipulating, processing, and grouping real-world data sets using Python.
• Information Visualization: This course teaches learners to use actionable dashboards in popular visual analytics platforms and present information to technical and non-technical audiences.
• Data and Database Management with SQL: This course teaches the SQL programming language, along with ways to organize and store data in relational database systems.
• Foundations of Machine Learning Models: Taught in Python, this class covers the definition of machine learning and its uses. Topics include regression and classification models and vector machines.

Cost and Payment Options for Data Analytics Master's Degrees

In the 2020-21 school year, the NCES found that the average graduate program cost $19,749. Like any national average, actual costs vary widely. Some online master's in data analytics programs cost less than $10,000 for the entire degree, while others can run higher than $65,000.

Many factors affect tuition prices, including the school's prestige, its public vs. private status, and your state residency. As a student, you may incur costs beyond tuition, such as fees, technology expenses, and additional necessities.

Scholarships, grants, employer reimbursements, and student loans can help cover these expenses. Talk with your college's admissions advisor, meet with your company's talent management staff, and fill out a FAFSA form to get your financial aid package started.

How Do You Choose a Data Analytics Master's Program?

Choosing the right master's degree in data analytics means looking deeper than a program's cost, length, and accessibility. Consider the following factors:

• Competitive Admissions: Research each prospective school's acceptance rate. How likely are you to be accepted?
• Location: Local employers may recognize a nearby school's value, and your fellow alums may have a more robust network in the area.
• Research Opportunities: Does the school maintain a modern laboratory? If you plan to work in research or academia, these resources can be critical.
• Final Project: Most master's degrees conclude with a thesis or an applied research project. Your school's final project requirements should correspond with your expectations.
• Career Services: How will your university help you create the tools and presence you need to secure a data analysis job after graduation?
• Earning Potential: Schools may track graduation rates, graduate employment statistics, and earnings six months after graduation.
• Accreditation: An institutionally accredited college holds accreditation from an agency recognized by the Council on Higher Education Administration or the Department of Education. Attending an accredited college gives you access to financial aid, transfer opportunities, and marketplace credentials.

More FAQ About Master's in Data Analytics

What is a master's in data analytics?

Building on the fundamentals of statistics, data analysis, and computer science, a 1-2 year master's in data analytics takes students deep into subjects such as multivariate analytics, data science tools, and applied machine learning.

Is earning a master's in data analytics easy?

Like any complex field, data analytics requires time, commitment, and the ability to master the subject. If you approach data analysis without a robust technical background, including programming and computer languages, you may find the degree especially challenging.

Which master's degrees are best for data analysts?

The "best" degree aligns with your personal and professional goals. An MS in data analytics focuses on the math and science of information collection and analysis. This degree prepares graduates for technology-focused jobs. An MBA in data analysis focuses on business leadership with a concentration in analytics, which might better suit aspiring business intelligence analysts.

What skills do I need as a data analyst?

You should develop a mix of hard and soft skills to work as a data analyst. For instance, while you should have strong SQL, statistical analysis, and data visualization skills, you also need to be a collaborative worker and critical thinker. The best master's in data analytics programs prepare you to handle complex data sets and present your findings intuitively.

How do I prepare for a data analytics master's program?

If your undergraduate major was not in computer science, statistics, or a related area, you may need to complete prerequisites before your graduate program. Try developing your math skills, learning a programming language, reading books on data science, or taking short online courses in data analytics.

All rankings and school descriptions on this page were created and reviewed independently by the TBS Rankings Team.