In a world drowning in data, there is a large and growing need for professionals with the expertise to translate that data into innovative business solutions. These professionals understand the business landscape in addition to analytics methods, and so can use analytics to address business problems, manage risk, and also to identify and create new business opportunities.
15 credits Four required courses and one elective course provide working knowledge in core business analytics methods and tools, from spreadsheets to relational databases to big data repositories, and their application to business problems across disciplines. One flexible elective enables individualized alignment with targeted career goals.
In addition, all students must pursue at least 3 credits of a 5000-level Management course.
Statistics in Business Analytics
This course offers an advanced level exploration of statistical techniques for data analysis. We shall study the concepts of population and sample; discuss the difference between population parameters and sample statistics, and how to draw an inference from known sample statistics to usually unknown population parameters. Topics will focus on rigorous statistical estimation and testing. The course will also prepare students with the skills needed to work with data using analytics software. (OPIM 5603, 3.0 credits).
In lieu of OPIM 5603, MBA students can take both BADM 5180/1.5 cr and OPIM 5181/1.5 cr to fulfill this 3 credit requirement)
Introduces the techniques of predictive modeling in a data-rich business environment. Covers the process of formulating business objectives, data selection, preparation, and partition to successfully design, build, evaluate and implement predictive models for a variety of practical business applications. Predictive models such as neural networks, decision trees, Bayesian classification, and others will be studied. The course emphasizes the relationship of each step to a company's specific business needs, goals and objectives. The focus on the business goal highlights how the process is both powerful and practical. (OPIM 5604, 3.0 credits)
Business Process Modeling and Data Management
Managing and improving a business process adds to the bottom line, and data is a core business asset derived from multiple business processes. The need to manage both efficiently and use them effectively has assumed paramount importance. This course introduces market-leading techniques that help to identify and manage key data from business processes. It provides the essential tools required for data mining and business process re-engineering. It combines lecture, class discussion and hands-on computer work in a business-oriented environment. (OPIM 5272, 3.0 credits)
Data Mining and Business Intelligence
Discusses data mining techniques that can be utilized to effectively sift through large volumes of operational data and extract actionable information and knowledge (meaningful patterns, trends, and anomalies) to help optimize businesses and significantly improve bottom lines. The course is practically oriented with a focus of applying various data analytical techniques in various business domains such as customer profiling and segmentation, database marketing, credit rating, fraud detection, click-stream Web mining, and component failure predictions. (OPIM 5671, 3.0 credits, prerequisite OPIM 5604)
Flexible Analytics Elective
- Choose at least one elective from the following list (OPIM 5XXX 3.0 credits):
- OPIM 5501 Visual Analytics
- OPIM 5502 Big Data Analytics with Hadoop
- OPIM 5503 Data Mining with R
- OPIM 5504 Adaptive Business Intelligence
- OPIM 5505 Analytical Consulting for Financial Services
- OPIM 5641 Business Decision Modeling
- 3 credits of other OPIM 5000-level coursework with permission