Master of Science in Business Analytics - Big Data Analytics (STEM) Shorelight Group - University of Massachusetts Boston, USA

UMass Boston's MS in Business Analytics (MSBA) is a 10 course, 30 credit degree program. To receive the MSBA, students must complete a minimum of 10 courses: Analytical Core, MSBA Electives, and the MSBA Capstone. One (1) prerequisite course must be satisfied or waived through prior relevant coursework, based on a review of transcripts.*

The MSBA program is designed to prepare students for utilizing analytical techniques, methods, and applications for data-driven practices in diverse organizations and enterprises of all sizes.

As businesses become more and more reliant on data-driven strategies, the needs and opportunities for graduates in Business Analytics have grown rapidly. Breakthroughs in data collection, storage, and analysis to uncover and capture business value have fueled this growth, and post-recession companies have recognized this potential and increasingly emphasize data-driven decision-making in their business strategies. The current annual rate of job growth in this area is approximately 11.8%, a rate that is only expected to accelerate in the future.

This program covers theories of powerful techniques and quantitative methods in Business Analytics and how they are applied in the real world. The program focuses on using current software tools to study effective techniques of problem formulation, developing solutions with mathematical and algorithmic techniques, and methods for implementing those solutions with technology.

The MSBA program offers students a choice of two specializations, Big Data Analytics and Supply Chain Analytics. Each includes a core of analytical courses, elective courses in that specialization, and a capstone course.

Big Data Analytics
The Big Data Analytics specialization focuses on data mining and analytical techniques, big data management, storage, and modeling. The objectives consist of enabling students to process big data in an effective and efficient way, discover knowledge patterns in big data, build predictive models, and use big data to answer business questions.