Modeling and Analytics

Catalog description

The widespread proliferation of IT-mediated economic activity generates a large amount of micro-level data about consumer, supplier, and competitor preferences. This has led to the emergence of a new form of competition based on the extensive use of analytics, experimentation, and fact-based decision-making. In nearly every industry, the competitive strategies that organizations are employing today rely extensively on data analysis to predict the consequences of alternative course of action, and to guide executive decision-making. This course provides a hands-on introduction to the concepts, methods, and processes of business analytics. Students will learn how to obtain and draw business inferences from data by asking the right questions and using the appropriate tools. Topics include data preparation, statistical tools, data mining, and the overall process of using analytics to solve business problems. Students will work with real-world business data and analytics software such as R. Students should also have a basic familiarity with elementary probability and be comfortable with basic data manipulation.