Knowing the difference between business analytics and data science will make choosing the best path for your career, easier.
Business Analytics Overview
Business analytics focuses on the application of data to draw insights and understanding that will be used to inform decision-making for businesses.
Business analytics professionals manage and take action on data. These professionals look for master programs that will equip them with both technical skills and business strategies to effectively manage and produce data and make decisions or recommendations for companies.
Business Analytics Background, Core Competencies, and Roles
A Master of Science in Business Analytics (MSBA) curriculum blends technical skills, such as R and SQL, analytic frameworks for interpreting data, and business strategies for translating insights into actions. The curriculum is integrated and comprehensive to optimize a student’s ability to analyze data and then use their business knowledge to make data-driven recommendations and decisions. Business analytics master programs are primarily made up of students with STEM backgrounds including computer science, mathematics, technology, information science, and statistics. However, they are more likely to accept a wider range of students as long as they are able to demonstrate strong data analytical and statistics skills.
Business analytics professionals will rely on the foundational analysis, data sets, and data acquisition done by data scientists to extract trends, interpret data insights, and make business recommendations. Moreover, business analytics professionals will be charged with choosing the correct analytical models to find solutions for their business, create visuals for raw data, and reports for management.
Some of the roles business analytics students fill include business analyst, operations research analyst, and market research analyst.
Data Science Overview
In comparison, the bedrock of data science lies in understanding and application of large data analysis, mining and programming that uncover and capture data for businesses.
A data scientist’s main role is to create and leverage data into a language that business analysts and other professionals can understand, and use, to extract and interpret trends. Data scientists use their skills to discover opportunities in data, such as in the design and structure of a database or the composition of a machine learning algorithm, that will in turn support business decision-making.
Data Science Background, Core Competencies, and Roles
A Master of Science in Data Science degree aims to sharpen and advance technical skills. Data science programs predominately focus on statistical modeling, machine learning, management and analysis of data sets, and data acquisition. While business analysts programs also train in these areas, they do not reach the level of nuance in training that data science students would.
A master‘s program in data science has firmer prerequisites about the type of major and course load students have taken in the past. They also demand more programming language competency before entering their programs. Masters in data science programs include computer science, mathematics, technology, information science, and statistics backgrounds.
Students with a masters in data science go on to fill roles as data architects, data scientists, data modelers, and data engineers.
The Difference between Business Analytics and Data Science for Your Degree Path
In conclusion, a degree in data science is a better career choice for individuals primarily interested in widening and focusing on tech language and data. Individuals interested in understanding the technical aspects of analytics and data, as well as their business applications to aid in decision making, are better suited by a business analytics program.
Is a business analytics program right for you? Check out upcoming admission events for the Master of Science in Business Analytics at the University of Washington, Foster School of Business.