Program Description
The B.S in Business Analytics is a multi-disciplinary program, working with the support of the Department of Mathematics & Computer Science and Department of Communicating Arts. This program includes a sequence of courses for students with strong analytical and quantitative abilities that they desire to use in business.
The Business Analytics program includes a wide range of topics including data visualization in business, database development and utilization, data mining, business forecasting, simulation-based decision making in business, regression analysis, and business statistics. As a major in the School of Business and Economics, the curriculum also includes the business core courses that are currently required for School of Business (SBE) majors. Students in the Business Analytics program will benefit from several High Impact Practices, including Senior Year Experience (capstone) courses and projects and experiential learning and community-based learning through required internships.
Student Learning Outcomes
The B.S. in Business Analytics provides students with strong analytical and quantitative abilities that are desirable in business. Students will develop new insights and understanding of business performance, based on data and statistical methods that will ultimately help business managers make optimal decisions and solve real world problems. Students will learn to use analytical and visualization tools to make important decisions and solve complex problems in the world of data. Students completing the B.S. in Business Analytics will gain the ability to:
- Identify business problems and opportunities using business analytic tools and techniques.
- Apply creative and critical thinking using data, information, statistics, and analytical models to solve business-related problems.
- Propose business solutions using data-driven decision-making process.
- Communicate the recommendations and solutions to the various stakeholders.
The program curriculum engages students to: study the past through descriptive analytics, predict what will happen and explain why it will happen, prescribe a solution, or make recommendations based on analysis, and utilize a wide range of software for analysis.
Faculty and Instructional Staff
Khadija Ajmal, Assistant Professor
Mei Cao, Professor
Kyle Roskoski, Teaching Associate Professor
