Master of Science in Business Analytics

This degree program provides students with the knowledge and essential skills needed to respond to the new challenges characteristic of the data intensive decision-making environments in the world today.

The program prepares students with the skills to handle large scale data, and develop and utilize statistical and analytics models to mine the data to gain business insights. This includes: cutting-edge analytical modeling; statistical analysis; data management techniques; emerging concepts, practices, and techniques in handling big data; data modeling and analysis to identify patterns; and applying skills to real-world problems in specific business domains. 

The program is one year and 30 credits. The curriculum offers a balance between foundational business concepts with skills in analytical and statistical modeling and data management. The curriculum includes three parts: a business core, an analytics core that includes both modeling and data management courses, and a domain-focused application core that includes project-based courses that allow students to apply their skills to real-world problems in specific domains.

This program is designed to provide hands-on experience through real-world problem solving. Academic partnerships with IBM and SAS, a business analytics software and services provider, will allow students to access a suite of software tools from these firms. Students will be able to use these software platforms in their courses to gain practical experience. Real-world data sets will also be used.

A two-semester Professional Development Workshop series is also required, to help students develop business communication, teamwork, leadership, and job search skills.

Outcomes of the Graduate Curriculum

Students who successfully complete this program will be able to:

• demonstrate a mastery of the quantitative elements of business analytics.
• correctly apply cutting-edge analytical modeling techniques (Analytics).
• construct data sets to address business problems (Data).
• demonstrate familiarity with emerging technologies and practices in handling big data (Technology).
• effectively visualize and display data (Visualization).
• communicate analytics insights in writing (Written Communication).
• create and deliver business presentations (Verbal Communication).
• demonstrate knowledge of key business functions related to analytics.