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Data Management covers fundamentals of relational database design, with special focus on data modeling and the use of SQL for relational data query and manipulation. Students need to be proficient at modeling business data, manipulating data through standardized query languages such as SQL, and accessing data from standardized database interface protocols

Intro to Data Analysis and Computational Statistics covers key statistical methods used to analyze data in support of business decisions and provides a practical introduction to modern techniques for computational data analysis using open source tools such as the R system.

Decision Support Systems focuses on model driven and data driven decision making tools that help managers address structured and semi-structured decision making tasks; management science topics include mathematical programming, decision theory, risk analysis and stochastic simulation; data-driven tools such as online analytical processing, business performance monitoring and probabilistic expert systems are considered.

Data Mining and Predictive Analytics provides in-depth coverage of data mining, the discipline concerned with extracting/discovering hidden patterns in the data. Data processing (including data reduction), data mining applications in real world situations are extensively addressed throughout the course.