Data Science Degrees: Analytics MBA vs. Master’s in Data Science

Data Science Degrees: Analytics MBA vs. Master’s in Data Science

Overview

A professional degree is often a requirement for data science jobs, and this demand has resulted in a growing number of universities offering data science master’s degrees and MBAs in business analytics/data analytics.

The two most common professional degrees for data scientists are an M.S. in data science and an MBA specializing in business analytics.

Although there is an overlap between these two types of programs, MBAs in analytics and data science Master’s have some marked differences.

A business analytics MBA, for example, generally focuses on data analysis and big data’s role in business. A data science Master’s program is much more scientifically-oriented, focusing on the math, statistics, programming, and experimental design used in data science and machine learning.

If you’re considering a professional degree in data science, you likely have these questions:

  • What is an analytics MBA?
  • What are the critical differences between analytics MBAs and an M.S. in Data Science?
  • Which type of degree should I pursue?

What is an MBA in data analytics?

The Master of Business Administration (MBA) degree is a professional, two-year degree traditionally offered through a university’s business school. When students enroll in an MBA program, they’re typically required to choose a specialization, which could include subjects like accounting, marketing, or economics.

However, in the last ten years, many schools have begun offering MBA data science specializations. These may be described as an MBA in data science, an MBA in data analytics, or a business analytics MBA.

This type of MBA program focuses on the intersection of business and big data; students learn how to use analytics and data science techniques to influence and impact business decisions and generate value for the company

Key Differences: Data Science MBAs vs. Master’s

While data science MBAs and Master’s degrees share similarities, there are distinct differences in curriculum and what you can expect to learn.

Generally, data science MBAs focus heavily on business analytics and intelligence. In other words, you’ll build domain expertise in how businesses can use data to influence business decisions and generate revenue.

The data science master’s degree, on the other hand, doesn’t necessarily have a business focus. Instead, these degrees cover various topics, including machine learning, statistical analysis, and even data visualization.

Data Science Master’s

Master’s in data science programs typically offer through a university’s computer science, math, or engineering department. Therefore, these degrees tend to be focused on the science of data science rather than the practical applications of data science in business.

These degree programs also dive deeply into foundation knowledge of data science, including concepts like statistical modeling and machine learning. A few key distinctions include:

  • Offered by university’s mathematics, engineering, or computer science schools
  • Scientifically driven, focused on mastering core data science concepts.
  • Dives deeply into programming, including coursework focused on SQL, Python, R, or Java
  • Focus on mathematics and statistics
  • Not necessarily focused on analytics or business; may include study in subject areas like public health or urban planning.

One thing to note: Many data science positions require business acumen. However, business sense can be learned on the job; however, many Master’s programs in data science offer business coursework.

Data Science MBA

Data science MBA programs are typically offered by a university’s business school and focus primarily on business analytics. These programs allow students to focus on using data science techniques in business to generate value and make informed decisions.

Like most MBA programs, the focus is on business theory. Therefore, data science is used to apply and study those business theories. Key differences include:

  • Offered by a university’s school of business
  • Business analytics or data analytics focused
  • The focus is on business theory, with data science as a tool for studying business theory
  • This may include coursework in data visualization, analytics, business intelligence
  • Typically looks at analytics’ use in marketing and business intelligence

Programming coursework varies by MBA program, and some require intermediate skills in languages like Python or SQL. Ultimately, if you pursue an MBA, you may have to supplement your programming studies with additional coursework or a boot camp.

Should you pursue a Master’s or MBA in data science?

Choosing to pursue a data science Master’s or MBA comes down to career goals and the type of work you want.

The data science MBA will better prepare you for this work if you’re passionate about business and learning how to apply data science to influence business outcomes.

Jobs for Analytics MBAs

If you’re interested in statistics and science or data science, for example, designing A/B testing experiments, then a traditional data science Master probably makes more sense. Generally, a business analytics MBA will prepare you for these types of data science roles:

  • Business analyst
  • Product manager/analyst
  • Marketing analyst
  • Business intelligence analyst
  • Growth marketing analyst
  • Business ops roles

One advantage of an MBA is that it offers more job diversity if you choose a career outside of data science. For example, an analytics MBA would also prepare you for finance, accounting, and marketing roles.

Jobs for M.S. in Data Science

A traditional data science Master’s prepares candidates for data science, machine learning, and research-related roles. You might choose a data science master’s degree if you’re interested in these roles:

  • Data/Machine Learning Engineer
  • Data Scientist
  • Research Scientist
  • Data Analyst
  • AI/Deep Learning Specialist

Build your business sense for data science jobs

Business acumen is a required skill for many data science jobs. Building business sense can typically be done on the job; however, dedicated coursework offers a chance to practice business data science skills.