Data Science vs. Business Analytics: Which Master’s Is Best?

Businesses, nonprofit organizations and government agencies the world over are increasingly reliant on data-driven decisions. Organizations seek to leverage vast datasets to gain insights into their operations, identify market trends and risks, and make informed strategic choices. This trend is behind a surge in demand for professionals skilled in data science and business analytics.

As a result, individuals considering careers in these fields can expect many career options, competitive salaries, and challenging, impactful projects on which to work. Data science and business analytics have much in common, but are there significant differences between data science and business analytics roles? Read on to explore those differences, including professional focus and career prospects. We'll also compare the structure and format of master's programs that train these data professionals.

What is Business Analytics?

Business analytics involves using statistical methods and computing technologies to analyze data, uncover patterns, and gain insights for better business decision-making. Key tools include data exploration, visualization, and integrated dashboards.¹

Business analysts work across many industries, with top employers in finance and professional services. Sample job titles include Business Intelligence Analyst, Competitive Intelligence Analyst, and Market Intelligence Consultant.²

What is Data Science?

Data science is a multidisciplinary field combining math, statistics, programming, AI, and machine learning to uncover actionable insights from data. It is vital for strategic planning in business, but also widely applied in fields like healthcare, finance, and environmental science.³

Skilled data science professionals are in high demand across diverse industries, including computer systems design and scientific research. Their work involves analyzing data, writing algorithms, and presenting insights to solve problems and guide decisions.⁴ Diverse job titles, such as Clinical Data Management Director, Data Architect, Machine Learning Scientist, and Business Intelligence Developer, reflect the range of industries where data scientists work.⁵

What is the Difference Between Data Science and Business Analytics?

Data science and business analytics, while related, differ in their methodologies, technical skills, and data types used. Understanding these differences can help you choose the right career path for you.

Methodologies

Data science employs advanced statistical methods, machine learning, and software development to explore open-ended questions. Data science job descriptions include building models and algorithms to derive insights and solve complex problems. In contrast, business analytics focuses on specific questions using established analytical techniques to improve processes and influence strategic decisions.⁶

Technical Skills

Data scientists need skills in programming languages, data management, and machine learning technologies to transform raw data into meaningful insights. They use tools like Python and R for analysis and visualization. Business analytics professionals benefit from skills in data visualization, stakeholder analysis, and business intelligence tools, focusing more on communication and strategic influence.⁷

Data Types

Data scientists handle large, complex data sets, often including structured and unstructured data, using statistical software for manipulation and analysis. Business analysts typically manage business, financial, or economic data, generating reports and dashboards, using mostly structured data, to aid business decisions.⁸

Business Analytics vs. Data Science Master’s Program Structures

Business analytics programs often cover data collection and mining, statistical analysis, and business modeling. Generally lasting 10–16 months, they are available both online and on-campus. The New York Tech Online Data Science, M.S. offers a fully online 30-credit curriculum focusing on programming, machine learning, and big data. Depending on the student's background, the degree can be completed in as few as 10 months.

Both business analytics and data science graduate degree programs may include independent projects or practical experiences. As discussed above, a major difference between business analytics and data science programs is the curriculum's focus. If the subject were cars, you could think of a business analytics program teaching you how to drive, while the data science degree teaches you how to build the engine.

New York Tech's Online Data Science, M.S. aligns with the recommendations of the Association for Computing Machinery (ACM) and provides you with deep knowledge of core data science topics, including:

• Computational theory
• Computer architecture
• Database systems
• Operating systems
• Computer algorithms
• Compiler design

Typical Admissions Requirements

Master's degree programs typically have admissions requirements that begin with proof of satisfactory completion of an undergraduate degree for admission. This means providing transcripts from your undergraduate program, and any additional graduate work you've done. The master's program will specify a minimum GPA for full acceptance and may have a provisional acceptance policy. It's not unusual for the master's program to require previous experience or course prerequisites.

The Online Data Science, M.S. at New York Tech requires a minimum undergraduate GPA of 2.85 on a 4.0 scale for unconditional acceptance. It may offer conditional admission for students with a GPA between 2.5 and 2.84. There are no technical experience or course prerequisites for admission. Qualified students who don't have sufficient background must take two prerequisite courses in programming and statistics before starting the core curriculum, along with completing a linear algebra course within six months of starting the program. An admissions outreach advisor can answer your questions about eligibility, program structure and more.

Comparing Earning Potential for Data Science and Business Analytics

Whether you go into business analytics or data science, you will find many career opportunities. Onet*online, the U.S. Department of Labor's database of occupational information, characterizes both as growing much faster than average.^8,2 The Bureau of Labor Statistics forecasts 36% growth in data science jobs from 2023-2033.⁹

Estimates for business analyst salaries vary widely and can be influenced by the industry, location, and a person's education and experience. ZipRecruiter reports a national average salary of $77,722.¹⁰ Glassdoor reports $142,521 in total compensation with $102,802 in base pay.¹¹

Data scientist salaries also vary based on location, industry, specific job role, and a person's education and experience. ZipRecruiter's national average is reported at $122,738,¹² and Glassdoor's is $160,586 in total compensation with a base pay of $115,471.¹³ The Bureau of Labor Statistics estimates median annual pay at $108,020.¹⁴

Making the Right Choice: Data Science or Business Analytics?

Only you can decide whether a business analytics or data science career path suits you. Data science and business analytics both drive data-driven decision-making, but they differ in scope and intent. Data science uses complex algorithms and data manipulation to answer complex questions, discover trends, and support strategic initiatives across industries. Business analytics focuses on interpreting data trends for developing business solutions, often with structured datasets and well-defined queries.

If you want to use your data skills for discovery and exploration, New York Tech's Online Data Science, M.S. can help you build industry-ready skills through a practical curriculum. With courses in machine learning, big data, and more, you'll prepare for satisfying, high-impact roles in diverse industries. Contact an admissions outreach advisor to learn more about how the program can help you reach your career goals.