Master’s in Data Science vs Business Analytics: What’s the Difference?

The COVID-19 pandemic has permanently changed the nature of business, forcing leaders to innovate under the pressure of unprecedented disruption.

Data science and business analytics both use data to generate insights and support better decision-making, but they differ in their focus and approach. Data science uses programming and mathematics to identify patterns within data and predict outcomes based on those patterns; meanwhile, business analytics combines analytical methods with business strategy to solve organizational challenges and guide high-stakes decisions.

These differences also shape graduate education options and career paths in each field. An in-person or online master’s in data science typically provides deeper technical training in areas such as machine learning, algorithms, and statistical modeling, while a master’s in business analytics places greater emphasis on applying analytics to business functions and developing leadership skills. This guide compares the two fields, their graduate degree programs, and potential career paths to help you determine which option best aligns with your goals.

The Difference Between Data Science and Business Analytics

“Data science” and “business analytics” are often used interchangeably to describe the process of analyzing data to make better business decisions, but there are significant differences between the two domains.

Here are some of the core differences between data science and business analytics:

• Scope: Data science is broad, with the goal of gathering high-level insights for business use, whereas business analytics is specific, with the goal of solving business problems and guiding business decisions.
• Objective: The objective of data analysis for business analytics professionals is to uncover trends and improve business decision-making. For data science professionals, on the other hand, the objective of data analysis is to understand what drives these trends and to predict future outcomes.
• Approach: Data science professionals approach their work through statistical and mathematical models, while business analytics professionals take an integrative approach, combining mathematical, operations, and business models.
• Communication: Professionals in either field must be able to communicate their insights to experts and stakeholders, but business analytics professionals must go one step further by developing and presenting actionable strategic recommendations.

Master’s in Data Science vs Business Analytics: Which Degree Should You Pursue?

Exploring the choice between a master’s in business analytics or master’s in data science program can be challenging since graduates of both degree programs develop expertise on how to gather and analyze data.

In general, an MS in Data Science offers an in-depth exploration of foundational programming and math concepts, centered on quantitative theory, while a MS in Business Analytics is more focused on business outcomes and provides knowledge of analytics skills and leadership techniques. The credit hours required and time for completion vary by university, but both programs typically range from 30 to 40 credit hours and might take anywhere from 1-2 years to complete.

Below, we outline an MS in Data Science vs an MS in Business Analytics, covering details on admission requirements, core courses, and learning outcomes for each of these program offerings.

Aside from factors related to curriculum and degree requirements, it’s critical to weigh other aspects that might be important to you. Some examples of program components you may want to consider based on your unique needs include:

• Program flexibility: If you are a working professional, you’ll want to consider an online master’s program that offers greater flexibility in your schedule.
• Experiential learning opportunities: A program that integrates a project-based Capstone is a great choice for those who value practical, real-world experiences.
• Specialization choices: Specialization options offer an opportunity to develop a niche skill set. Some examples of program specializations for an MS in Data Science are “Business Analytics” and “Information Systems.”
• Networking experiences: For those who value the importance of establishing professional connections at graduate school, a program with a strong network of industry-connected alumni and faculty can be a good choice.

Careers with a Master’s in Data Science

Remember those businesses that are investing in analytics projects but aren’t seeing the results they expected? They’re becoming more aware of the mishaps that can occur if they don’t have experts on their team who can bridge the data skills gap in their organizations. Students earning a master’s in data science are equipped to fill these roles and can expect to to launch a career in one of the most sought-after fields in the world.

According to the U.S. Bureau of Labor Statistics (BLS), employment of data scientists is expected to grow by 22% between 2025 and 2035, placing it among some of the fastest growing occupations today. Those considering a career in data science can also look forward to a substantial salary, as the average annual earnings for data scientists was $140,300 in 2025.

A master’s degree is generally required for entry-level data science jobs, as it gives you the training necessary for this technical field. The following are some in-demand positions for graduates of master’s in data science program:

• Data scientist
• Machine learning engineer
• Computer systems analyst
• Data architect
• Statistician
• Data engineer

Learn more about what you can do with a Master’s in Data Science.

Careers with a Master’s in Business Analytics

According to PayScale, the average salary for master’s in business analytics holders is $82,000 per year— higher than those at the bachelor level. Like data scientists, business analysts are in high demand, with expected job growth of 10% between 2025 and 2035.

While entry-level jobs commonly require a bachelor’s degree, a master’s can boost your career and increase your earning potential. Common master’s in business analytics job positions include:

• Management analyst
• Data analyst
• Market research analyst
• Business intelligence developer
• Project manager
• Operations research analyst

About the Online MS in Data Science at Pace University

The Pace University online Master of Science in Data Science was designed to help students take advantage of professional opportunities in the next generation of quantitative solutions. Our STEM-designated curriculum leverages the Seidenberg School’s decades of experience in online education to explore theoretical and practical approaches to data governance, machine learning, predictive analytics, and more. This flexible, 100% online program fits a combination of hands-on experience and asynchronous activities into your schedule, building the expertise you need to guide the future of data-driven organizations. Pace University also offers an on-campus option for the MS in Data Science.

Learn more about the Online MS in Data Science, or get started on your application today.