Grad Prereq: IS710/711/716; IS823 recommended
The widespread proliferation of IT-influenced economic activity leaves behind a rich trail 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 virtually every industry the competitive strategies organizations are employing today rely extensively on data analysis to predict the consequences of alternative courses of action, and to guide executive decision making. This course provides a hands-on introduction to the concepts, methods and processes of business analytics. We will learn how to obtain and draw business inferences from data by asking the right questions and using the appropriate tools. Topics to be covered include data preparation, data visualization, data mining, text mining, recommender systems as well as the overall process of using analytics to solve business problems, its organizational implications and pitfalls. Students will work with real world business data and analytics software. Where possible cases will used to motivate the topic being covered. Prior courses in analytics, data management and statistics (such as IS823) will be helpful but are not required.
[ 3 cr.]
Offered: 1st sem.