Data Mining for Business

Catalog description

Intended for recent graduates with little to no professional experience, BAN 841 develops business students¿ understanding of and ability to apply a variety of data mining tools and techniques for use in detecting and exploiting patterns and relationships in large structured and unstructured data sets derived from a variety of business scenarios. Students will explore the use of cluster analysis, classification, association, and cause-and-effect modeling techniques to explore and reduce data, classify new data elements, identify natural associations among variables, create rules for target marketing or buying recommendations, and describe relationships among data that motivate business performance. Specific techniques may include k-nearest neighbor, discriminant analysis, and association rule mining. Students will learn how to bridge descriptive and predictive analytics across a variety of business scenarios. Coursework includes individual assignments intended to develop confidence with basic data mining techniques, followed by case-based problems that challenge students¿ creativity and data mining mastery in search of patterns and data relationships leading to useful business insights. While underlying theory will be discussed, the course will prepare business analysts by focusing specifically on data mining applications in marketing, finance, supply chain management, and other business areas, with an emphasis on the unique aspects of decision making in a business environment. Software packages, concepts, and business applications will vary and evolve to keep pace with technology, theory, and instructor interest.