Business Systems and Analytics (M.S.)

This course focuses on data warehousing and data mining in organizations. Topics covered in the course include: data warehousing and mediation techniques aimed at integrating distributed, heterogeneous data sources; data mining techniques such as rule-based learning, decision trees, association rule mining, and statistical analysis for discovery of patterns in the integrated data; and evaluation and interpretation of the mined patterns using visualization techniques.

This course introduces today’s most valuable marketing research and analytics methods and tools and offers a best-practice methodology for successful implementation. Hands on projects and case studies provide students an opportunity to apply the marketing research and analytics techniques for solving key problems, ranging from product development, segmentation, pricing, campaign management, brand valuation, and digital marketing strategy.

This course is about the manager’s responsibilities for problem solving and decision making, and those areas in which information technology can be used to gain the insight needed to support selection of decision alternatives. Students learn about the role of data, information and knowledge in managerial problem solving and decision making. Transactional processing and database management systems (DBMS) are used to store, manage and retrieve data in organizations. Decision support system (DSS) tools and technologies (such as natural language programming and influence diagramming) are used to organize data into information for decision analytics. Expert systems (ES) are used to synthesize information into knowledge for knowledge management. Students are required to use DBMS, DSS and ES software packages in a hands-on environment.