The fields of business analytics and data science share the goal of using large amounts of data to understand information and solve problems. The most significant differences between data science and business analytics are the level of technical knowledge required of practitioners and how that knowledge is used.
Syracuse University offers master’s programs online in both fields: a Master of Science in Business Analytics taught by faculty in the Martin J. Whitman School of Management, and a Master of Science in Applied Data Science taught by faculty in both the Whitman School and the School of Information Studies.
Through the Master of Science in Business Analytics, students learn how to interpret data to improve processes. Students may end up assuming roles in which they use their knowledge to guide their organizations in making evidence-based, actionable business decisions. The Master of Science in Applied Data Science helps students better understand complex data, applying analytical and technical skills to execute data-driven decisions. As a result, a number of career opportunities outside of data analysis exist for professionals with a data science degree.
Learn about other career opportunities outside of a data analyst that exist for professionals with a data science degree
Master’s in Business Analytics vs. Data Science Learning Outcomes
In both data science and business analytics programs, students will learn how to gather and analyze data. The difference lies in how this analysis is applied. Data science students delve deeper into the data, focusing on how to organize it, gleaning insight from the information and explaining what it means to others. By comparison, business analytics students develop a foundational understanding of the data, derive insights and use those insights to make decisions that drive positive business outcomes.
Business Analyst vs. Data Scientist Requirements
The education requirements to become a data scientist vs business analyst differ slightly. Most data scientists pursue a master’s degree before entering the field, while many business analysts launch their careers with just a bachelor’s degree. That said, the M.S. in Business Analytics can help general business professionals advance into a more specialized, data-oriented role. Read on to learn more about the difference between data science and business analytics requirements.
Business Analyst Requirements
Want to know how to become a business analyst? The first step in launching a business analyst career is completing the necessary education requirements, namely a bachelor’s degree in business, finance or a related field. For some employers, business analyst degree requirements might include a master’s in business administration or business analytics. Depending on the role, employers may also list additional business analyst requirements in their job descriptions, like experience or familiarity with specific software and applications.
A master’s degree can help you acquire these skills and others through a rigorous business analyst education. With Syracuse University’s master’s in business analytics online, you learn foundational data skills and the methods for applying them in a business setting to help position your organization for success.
Data Scientist Requirements
Most data scientists complete an undergraduate degree and a master’s degree before entering the field, a process that typically takes six to seven years. While some employers only require a bachelor’s degree, others prefer a master’s or doctoral degree. In fact, a 2017 IBM study [PDF, 3.9MB] found that 39 percent of data science job postings listed a master’s degree or Ph.D. among their data scientist requirements. That said, there’s no definitive guide on how to become a data scientist. If you learn the technical skills to analyze and communicate data, you might be able to get your foot in the door without a formal degree—as long as you have projects and experience to prove your potential.
While everyone’s career path looks different, many aspiring data scientists find a master’s degree useful to gain in-demand technical skills that are applicable across industries. Syracuse University’s online Master of Science in Applied Data Science will help aspiring data scientists acquire the skills necessary to stand out in the job market, including data analysis, cloud management and text mining—along with other data scientist degree requirements.
Data Science vs. Business Analytics Courses and Curriculum Structure
Students in the master’s in data science and the master’s in business analytics programs are required to take core courses and analytics application courses, with some courses overlapping across the two programs. However, the business analytics program allows greater flexibility for students with career goals beyond just analytics, requiring fewer technology-focused courses and offering a wide variety of electives in technical and business topics. The data science program requires several courses in more technical topics and only offers electives that focus on technology and analysis.
Business Analytics Curriculum
The business analytics curriculum is driven more by the student’s goals.
- Core courses: Students take two core analytics courses and four courses that apply analytics to essential business areas.
- Elective courses: Students choose six in-depth electives from The Whitman School of Management and School of Information Studies. These include technical courses such as data warehousing and data analytics, as well as business courses such as strategic brand management and finance.
Learn more about the curriculum for Syracuse University’s Master of Science in Business Analytics.
Data Science Curriculum
The data science course sequence is much more focused on the how-to of data science.
- Core courses: There are six required core courses in analytical topics, including data mining and big data analytics. Students must then choose one or two courses in applying analytics to business-related fields.
- Elective courses: Students also must select four or five electives, which include technical topics such as text mining and natural language processing.
Learn more about the curriculum for Syracuse University’s Master of Science in Applied Data Science.
Data Scientist vs. Business Analyst Career Outcomes
The choice between business analytics and data science ultimately comes down to a student’s post-graduation career goals. Below are examples of career options for graduates of each program.
What Does a Data Scientist Do?
Many students in master’s in data science programs pursue roles in fields such as engineering and IT. They may be employed as data scientists/engineers, statistical programmers or database administrators. In these more technical roles, professionals manage large amounts of data, create visualizations and design and deploy algorithms that support decision-making tools.
Potential data science responsibilities include:
- Finding opportunities in data sets by mining data and writing algorithms to support decision-making processes.
- Creating an analysis foundation that can help others solve business problems.
- Managing large data sets by using methods such as linear discriminant analysis and multilinear regression selection.
- Designing and structuring databases.
What Does a Business Analyst Do?
Typically, students in the master’s in business analytics programs desire greater business experience and specialized knowledge to lead their team or organization. They may work as business analysts or analytics managers, or they may need analytics knowledge to advance in marketing or accounting teams. In these roles, professionals extract data to explain trends, predict future performance, determine best approaches and explain solutions to stakeholders.
Potential business analyst responsibilities include:
- Sparking change by turning data analysis into tangible resources for decision-making.
- Defining business problems and translating statistical analysis into business intelligence that improves performance.
- Interpreting and visualizing raw data to make it digestible and accessible for business users.
- Integrating and suggesting solutions that use data modeling.
- Defining and aligning database requirements.
Business Analytics vs. Data Science Salary
Before deciding on a career path, it’s helpful to know more about a data scientist vs business analyst salary. According to data from the Bureau of Labor Statistics (BLS), data scientists tend to earn more than business analysts, but there are a number of factors that determine pay. Your salary can be higher or lower depending on who you work for, where you live and how much experience you have. This is important to keep in mind while weighing the pros and cons of an M.S. in Business Analytics vs an M.S. in Applied Data Science.
Business Analyst Salary
Curious about a typical business analyst salary? According to 2020 BLS data, business analysts had a median annual salary of $87,660, while the highest 10 percent of business analysts earned more than $156,840. In addition to a substantial business analytics salary, these professionals enjoy considerable job security. The BLS projects job growth of 14 percent for business analysts from 2020 to 2030, faster than the average for all occupations.
Data Scientist Salary
Like business analysts, data scientists enjoy above-average salaries and job growth. BLS data indicates that, on average, a data scientist salary was $126,830 per year in 2020, with the highest 10 percent earning more than $194,430. According to the BLS, the typical entry-level education for the field is a master’s degree, so a master’s in data science salary may be higher than salaries for those without a post-bachelor’s education. Between 2020 and 2030, expected job growth for data science professionals is 22 percent—even higher than that for business analysts.
Should You Pursue a Degree in Data Science or Business Analytics?
If you’re still debating whether to pursue a master’s in business analytics vs data science, rest assured: both degrees can prove useful in a variety of settings. The decision between a career in business analytics vs data science ultimately comes down to your educational background, skill set and professional interests and goals.
If you’re a business professional aspiring to interpret data, explain trends and make better decisions on behalf of your team, the M.S. in Business Analytics program may be right for you. On the other hand, those interested in developing skills in statistics and computer programming to join an engineering or IT department will likely find the M.S. in Applied Data Science program to be the best fit for them.
Data Science and Business Analytics Admissions
Both the data science and business analytics programs require 36 credits and can be completed in as few as 18 months. GRE or GMAT scores are required for both programs, but students with sufficient professional experience may be eligible for a waiver. In addition, GMAT waivers are available for business analytics applicants if they have at least one year of professional work experience and an undergraduate GPA of 3.0 or above, an undergraduate degree in select fields or a master’s in any field. Learn more about the admissions for Syracuse University’s M.S. in Business Analytics and M.S. in Applied Data Science programs.
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