The Master of Science in Data Analytics program prepares students to be strong organizational leaders by using business intelligence and data analytics. Students learn to improve decision-making and business processes in core business functions such as accounting, finance, logistics, management, and strategy through the application of business intelligence solutions and data analytics principles. The importance of data security, privacy, and the ethical treatment of data is enforced. Technical topics include data warehousing, data mining and visualization, business analytics, predictive analytics, and enterprise performance management. The program prepares students for careers such as business/systems analysts, business intelligence developers/analysts, ETL developers, data analysts, data architects, and data scientists.
Program Specific Admission Requirements
In addition to the institutional graduate admission standards, students seeking admission to the MSDA program must have an undergraduate degree with a major or concentration management information systems, information technology, computer science, or database management and demonstrate that they have recently (last 5 years) taken at least introductory courses in the following three areas: computer programming, database management, and statistics.
Students who do not meet the above conditions may be admitted provisionally to the program. A course(s) from the list below may be required to be completed as a prerequisite to the MSDA coursework to build up background knowledge in these areas:
- MIS470: Data Science Foundation
- MIS445: Statistics in Business Analytics
- MIS407: Database Concepts
- ITS320: Basic Programming
- To gain full admission to the MSDA program and begin graduate level coursework, provisionally admitted students must complete assigned prerequisite course(s) within 12 months of starting with a minimum cumulative grade point average of 3.0. All coursework must also be completed with a grade of ‘C’ or higher. Students need a computer that has a 64-bit hardware and software platform.
Recommended order of courses for the Master of Science in Data Analytics program:
Note: This order of courses is based on the Winter 2019 catalog. If you started this program prior to the Winter 2019-2020 trimester, you may have a different list of required classes. Please refer to a previous academic catalog to view your required courses. You can view your catalog year from your Student Portal by clicking on Degree Progress Details. All previous catalogs are available in the Student Portal, on the bottom of the main page.
- (RES500*: Fundamentals of Quantitative Analysis) *(Not required for all students)
- MIS500: Foundations of Data Analytics
- MIS540: Introduction to Business Intelligence
- MIS510: Data Mining and Visualization
- MIS530: Predictive Analytics
- MIS541: Data Warehousing in Enterprise Environments
- MIS542: Business Analytics
- MIS543: Enterprise Performance Management
- MIS581: Capstone - Business Intelligence and Data Analytics
- 12 Specialization Credits
- MIS595* - International Management Internship (optional course)
*MIS595 is an optional course that provides students with practical data analytics experience. This course may not be available in all states; see the State Specific Authorization Policy under Admissions Policies.
For course descriptions, please visit the current academic catalog.
If you are an M.S. in Data Analytics student in the pre-requisite group and you are using financial aid, you will see differing loan availability. Please see below for how this status will impact your aid and your responsibilities as a student in this group:
- M.S. in Data Analytics students will be packaged at 4th year undergraduate funding levels while completing the prerequisite courses and are still held to undergrad aggregate limits ($57,500)
- Students in the pre-req group will need to meet undergraduate half-time status (6 credits) in a trimester to be eligible for financial aid
- Once prerequisites have been fulfilled, and your are fully moved to the M.S. in Data Analytics, you will be eligible for a grade level increase to graduate level funds**
**Can only increase grade level between trimesters, not mid trimester