Business Analytics (MS)
The Master of Science in Business Analytics offers a unique blend of courses with a strong focus on data analytics–and it can be completed in one year.
This STEM-designated degree emphasizes important skills and tools in the information systems and analytics space such as SQL, Python, R, Tableau, database and data warehouse modeling, data mining, data visualization, and data storytelling.
CURRICULUM
The 12-course curriculum of the Master of Science in Business Analytics prepares you to be a responsible leader in the fast-growing information systems and analytics fields.
Courses are offered in online, hybrid, and in-class formats. Students can complete all 12 courses in one year and completely online.
All MS students will be awarded the Business Analytics Certificate as well. The Business Analytics certificate is a 5-course graduate Quinlan program, and all its courses are a part of the MS program.
Students with previous information systems coursework and part-time students should contact Nenad Jukić, the program director, for more information on how their courses would be sequenced.
| Code | Title | Hours |
|---|---|---|
| Required Courses 1 | ||
| INFS 443 | Business Analytics | 3 |
| INFS 492 | Database Systems | 3 |
| INFS 494 | Data Mining | 3 |
| INFS 592 | Data Visualization | 3 |
| INFS 791 | Programming for Business Decision Making | 3 |
| INFS 796 | Data Warehousing | 3 |
| ISSCM 491 | Managerial Statistics | 3 |
| Electives | 9 | |
Group One (Take up to 5 Courses) | ||
| Business Requirement Analysis | ||
| Strategic Use of Database Analytics | ||
| Principles of Analytic Programming | ||
| Applications of Visualization | ||
| Quality in Product Management | ||
Group Two (Take 0 to 4 Courses) 2 | ||
| Game Theory & Strategy | ||
| Derivative Securities | ||
| Applied Econometrics | ||
| Investment Management | ||
| Applied Portfolio Management | ||
| Interest Rate Risk Management | ||
| Credit Risk Management and Structured Finance | ||
| Analytical Problem Solving | ||
| Forecasting Methods | ||
| Project Management | ||
| Data Driven Decision Making | ||
| Research Methods in Marketing | ||
| Digital Marketing | ||
| Database Marketing Strategy | ||
| Customer Analytics | ||
| Marketing Metrics | ||
| Intro to Operations Management | ||
| Global Logistics | ||
| Purchasing Management | ||
| Inventory Management | ||
| Supply Chain Analytics | ||
| Ethics Requirement (Take 1 Course) | 3 | |
| Business Ethics | ||
| Ethics and Data Analytics | ||
| International Business Ethics | ||
| Practicum | 3 | |
| Select one of the following: | ||
| Applications of Visualization | ||
| Quality in Product Management | ||
| Capstone Master of Business Data Analytics | ||
| Total Hours | 36 | |
- 1
Some courses may be substituted based on previous coursework with the permission of the program director.
- 2
Additional courses may be approved by the program director.
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.
| Year 1 | ||
|---|---|---|
| Fall | Hours | |
| INFS 492 | Database Systems | 3 |
| INFS 795 | Ethics and Data Analytics | 3 |
| ISSCM 491 | Managerial Statistics | 3 |
| Hours | 9 | |
| Winter | ||
| INFS 443 | Business Analytics | 3 |
| INFS 485 | Business Requirement Analysis | 3 |
| INFS 796 | Data Warehousing | 3 |
| Hours | 9 | |
| Spring | ||
| INFS 494 | Data Mining | 3 |
| INFS 592 | Data Visualization | 3 |
| INFS 691 | Principles of Analytic Programming | 3 |
| Hours | 9 | |
| Summer | ||
| INFS 493 | Strategic Use of Database Analytics | 3 |
| INFS 791 | Programming for Business Decision Making | 3 |
| INFS 797 | Applications of Visualization | 3 |
| Hours | 9 | |
| Total Hours | 36 | |
Graduate & Professional Standards and Regulations
Students in graduate and professional programs can find their Academic Policies in Graduate and Professional Academic Standards and Regulations under their school. Any additional University Policies supersede school policies.
LEARNING OUTCOMES
At the completion of the program, graduates are expected to:
- Use data to drive strategic and tactical business decisions;
- Utilize sophisticated database, data warehousing, data mining, and data visualization methodologies and techniques to capture and apply data as a corporate asset;
- Demonstrate competence with various languages and tools, SQL, R, Tableau, and Python;
- Lead, supervise, and manage information systems projects of varying levels of complexity;
- Demonstrate effective communication skills with technical and non-technical individuals and groups;
- Show ability to effectively collaborate with and provide technical leadership to a variety of business units and organizations;
- Demonstrate a high level of technical aptitude in design, development, and use of information systems components;
- Integrate values and ethics into data analysis and information systems projects and solutions.