Business Data Analytics (MSBDA)
Position yourself as a data-driven business leader—and your company’s data scientist—with an MS in Business Data Analytics.
This one-year, full-time graduate degree program will prepare you to make informed business decisions based on a targeted analysis of the data available to business today.
Related Programs
Learn which of our analytics programs best fits your needs through our analytics degree program comparison.
Curriculum
The Master of Science in Business Data Analytics 12-course curriculum prepares you to be a responsible leader in the fast-growing field of business data analytics—in just one year.
| Code | Title | Hours |
|---|---|---|
| MBA Prerequisites | ||
| ISSCM 400N | Quantitative Methods I | 0 |
| ISSCM 402N | Quantitative Methods II - Statistics Primer | 0 |
| MBA Introductory courses | ||
| ACCT 400 | Financial Accounting for Business Decisions | 3 |
| ECON 420 | Managerial Economics | 3 |
| FINC 450 | Financial Management | 3 |
| MARK 460 | Marketing Management | 3 |
| SCMG 480 | Intro to Operations Management | 3 |
| MBA Required Courses | ||
| FINC 470N | Business Finance | 3 |
| HRER 417N | Managing and Motivating in the Workplace | 3 |
| ISSCM 596N | Data Driven Decision Making | 3 |
| MARK 425N | Business Communication | 1.5 |
| MGMT 426N | Leadership Development | 1.5 |
| MARK 470N | Research, Insights and Storytelling | 3 |
| MGMT 430N | Strategy and Leadership | 3 |
| MGMT 431N | Business Consulting Course | 3 |
| MSBDA Required courses | ||
| BSAD 499 | Special Topics | 3 |
| BSAD 699 | Capstone Master of Business Data Analytics | 3 |
| FINC 620 | Financial Mathematics and Modeling I | 3 |
| INFS 492 | Database Systems | 3 |
| INFS 494 | Data Mining | 3 |
| ISSCM 491 | Managerial Statistics | 3 |
| ISSCM 495 | Forecasting Methods | 3 |
| or FINC 625 | Applied Econometrics | |
| Ethics course | 3 | |
| Select one of the following: | ||
| Ethics and Data Analytics | ||
| Business Ethics | ||
| International Business Ethics | ||
| Elective Courses | 12 | |
| Choose four electives from the following three areas, with at least one elective from each of the areas. | ||
| Economics/Finance | ||
| Business Fluctuations | ||
| Game Theory & Strategy | ||
| Derivative Securities | ||
| Investment Management | ||
| Applied Portfolio Management | ||
| Interest Rate Risk Management | ||
| Credit Risk Management and Structured Finance | ||
| Valuation | ||
| Marketing Management | ||
| Research Methods in Marketing | ||
| Customer Analytics 1 | ||
| Marketing Metrics 1 | ||
| Analytical Problem Solving | ||
| Information Systems and Supply Chain Management | ||
| Data Visualization 1 | ||
| Data Warehousing 1 | ||
| Project Management | ||
| Intro to Operations Management | ||
| Global Logistics | ||
| Purchasing Management | ||
| Inventory Management | ||
| Supply Chain Analytics | ||
| Total Hours | 72 | |
- 1
Recommended courses.
Suggested Sequence of Courses
The below sequence of courses is meant to be used as a suggested path for completing coursework. An individual student’s completion of requirements depends on course offerings in a given term as well as the start term for a major or graduate study. Students should consult their advisor for assistance with course selection.
| Master's | ||
|---|---|---|
| Term 1 | Hours | |
| Prerequisite Courses | ||
| ECON 420 | Managerial Economics | 3 |
| FINC 450 | Financial Management | 3 |
| MARK 460 | Marketing Management | 3 |
| Hours | 9 | |
| Term 2 | ||
| FINC 620 | Financial Mathematics and Modeling I | 3 |
| ISSCM 491 | Managerial Statistics | 3 |
| Select one from Electives | 3 | |
| Hours | 9 | |
| Term 3 | ||
| BSAD 499 | Special Topics | 3 |
| INFS 492 | Database Systems | 3 |
| Select one from Electives | 3 | |
| Hours | 9 | |
| Term 4 | ||
| INFS 494 | Data Mining | 3 |
| ISSCM 495 | Forecasting Methods | 3 |
| Select one from Electives | 3 | |
| Hours | 9 | |
| Term 5 | ||
| BSAD 699 | Capstone Master of Business Data Analytics | 3 |
| MGMT 441 | Business Ethics | 3 |
| Select one from Electives | 3 | |
| Hours | 9 | |
| Total Hours | 45 | |
Learning Outcomes
- Gain a deep understanding of some of the tools and software that are used in modern day analytics
- Be able to transform large data sets into insightful and actionable information in an easy-to understand format to assist organizational decision making using advanced analytical tools
- Develop skills in forecasting, modeling and problem solving
- Develop experience tackling industry-specific problems and challenges using advanced analytics and computational methods