A master’s in data analytics prepares you for a career in data analytics, whether you’re an established professional or someone looking to start a new career. As a result, a Master of Science (MS) in Data Analytics program can cover introductory to advanced courses, allowing course takers to learn new skills or deepen old ones.

Learn more about master’s degrees in data analytics, whether you should consider pursuing one, and the different types of degrees available. Then, you’ll find suggested courses to help you get started today. 

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Overview: What can you do with a master’s in data analytics?

A master's degree in data analytics can help you enter the field, shift your career, or advance your current professional path by attaining a higher educational qualification. In effect, a master's degree in data analytics can either supplement undergraduate work in the field or provide the groundwork for a career shift if you study another discipline.

Discover what you need to know about a data analytics degree, how it compares to similar degrees, and what you can expect from it.

Master’s vs. bachelor’s degree in data analytics 

A master’s degree shares many similarities with a bachelor’s degree in data analytics. But, keep in mind some key differences.

Generally, a master’s and bachelor’s degree in data analytics will cover much of the same material, such as data analysis, computer science, and statistics. However, some master's programs may cover these topics in greater depth than you would encounter in an undergraduate course.

But, while the programs might cover much of the same material, they usually do so within very different timelines. For example, while a bachelor's degree usually takes four or more years to complete, a master's degree can take just one to two years, depending on the program, your course load, and whether you're a full- or part-time learner. To enroll in a master's program, you'll already need a bachelor's degree.

Curriculum

The exact curriculum that you’ll follow as a graduate learner in data analytics will vary from program to program. Still, you can expect to take courses in such common topics as data analysis,  statistics, computer science, and machine learning.  

To help you better understand what you can expect from a master’s program, consider the curriculum for Oregon State University’s Master of Science in Data Analytics program [1]:

• 45 credits on topics such as computer science, statistics, and statistics electives. Required courses include:

  • Foundations of Data Analytics

  • Data Analytics

  • Data Analytics II

  • Multivariate Analytics

  • Time Series Analytics

  • Capstone Project

  • Programming and Data Structures

  • Data Science Tools and Programming

  • Applied Machine Learning

  • Plus 12 credits of electives

• Oral examination in which you will defend your capstone project

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Google Data Analytics

Get on the fast track to a career in Data Analytics. In this certificate program, you’ll learn in-demand skills, and get AI training from Google experts. Learn at your own pace, no degree or experience required.

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Spreadsheet Software, Data Management, Data Analysis, Business Communication, General Statistics, Business Analysis, Data Visualization, SQL, Problem Solving

Is a master’s in data analytics worth it? 

Depending on your own goals, resources, and background, an MS in data analytics could be well worth the effort. Or, it could be an unnecessary detour you don’t need to get where you want to be. Typically, a master’s is well-suited for individuals who don’t already possess a bachelor’s degree in data analytics or who wish to continue studying data analytics from an academic perspective. Individuals who previously received a bachelor’s degree in a related field, like statistics or computer science, might consider obtaining a master’s in data analytics to gain a deeper understanding of the field and to market their skill set to potential employers. 

According to Zippia, the percentages of data scientists with a bachelor’s, master’s, or doctoral degree are as follows [2]:

• Bachelor’s degree: 51 percent

• Master’s degree: 34 percent 

• Doctoral degree: 13 percent

This educational breakdown suggests that a bachelor’s degree could be sufficient for job seekers to land a role. However, a master’s could positively highlight your skills and abilities to employers, making you a more competitive applicant overall. Sometimes, an employer may even explicitly require a master’s degree for senior positions. 

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Google Advanced Data Analytics

Learn in-demand skills like statistical analysis, Python, regression models, and machine learning in less than 6 months.

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Master’s in data analytics salary 

According to the US Bureau of Labor Statistics (BLS), the higher a degree someone holds, the more they’re likely to earn. In its “Education Pays, 2023” study, for instance, the BLS breaks down the median weekly pay for various degrees as follows [3]: 

While this research does not specifically focus on master’s degrees in data analytics or a related profession, it does suggest that a graduate degree could positively impact your earning potential.

Are data analysts in demand?

Yes, data analysts are in high demand. The BLS predicts that the job outlook for data scientists will grow by 36 percent between 2023 and 2033, which is much faster than average. Further, the BLS anticipates 20,800 job openings in the field every year during that same period [4].

Data analytics jobs

A degree in data analytics can prepare you for a variety of jobs. While you can attain some of these jobs with a bachelor’s degree in data analytics, more senior roles may require an advanced degree, such as a master’s degree. 

Consider these positions to pursue with a master’s in data analytics: 

• Data analyst 

• Business analyst 

• Data scientist 

• Statistician 

• Business systems analyst

• Business intelligence analyst

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Master’s in data analytics program comparisons

You may have numerous reasons to pursue a master’s degree in data analytics and a wide range of different types of master's degrees that you can pursue. If you’re considering a future as a graduate learner, then you’ll want to consider these three types of programs before applying: 

In-person master’s degree in data analytics 

An in-person master’s degree program is where you attend classes alongside your peers in a real-world classroom. As a result, this option provides a more traditional college experience, including more face-to-face time with your peers and instructors, often allowing you more direct guidance and networking opportunities. However, in-person degrees often cost more and are more rigidly structured than other program types. 

Master’s in data analytics online

Online master’s programs are becoming increasingly popular due to the flexibility they provide course takers and their often lower cost of attendance. While some programs may follow traditional application timelines, others might have more relaxed admissions requirements that allow applicants to apply on a rolling basis. However, while these programs usually provide more flexible schedules and cost less, you may experience fewer opportunities for networking and mentorship than more traditional options. 

Hybrid programs 

A hybrid graduate program pairs elements of in-person and online programs to provide greater flexibility in completing course material while allowing for more networking opportunities. Depending on your circumstances and personal objectives, a program of this nature could either offer the best of both worlds or be a more compromised version of your ideal program that doesn’t fit your needs.  

Learn more before earning your data analytics degree.

Studying data analytics prepares you for many rewarding career opportunities. To master data analytics, you need to learn all you can. If you're considering a career in data analytics, you might consider taking an online specialization through Coursera. 

The University of Michigan’s Data Analytics in the Public Sector with R Specialization equips course takers with fundamental technical skills using the R programming language to gather, manipulate, analyze, visualize, and interpret data to inform public policy and public administrative functions.

Macquarie University's Excel Skills for Data Analytics and Visualization Specialization, meanwhile, teaches course takers how to bring data to life using advanced Excel functions, creative visualizations, and powerful automation features. 

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