Data Analytics for Business Information Systems. 3 credits, 3 contact hours

Catalog description

Prerequisites: ( CS 100 or DS 100 ), and ( MATH 105 or MATH 120 or MATH 225 or MATH 244 or MATH 279 or MATH 305 or MATH 333 or IE 331 or ECE 321 or MGMT 116 or MNET 315 ), and ( CS 331 or IS 331 or MIS 385 ). This course introduces students to the world of business analytics from an information systems perspective, focusing on the application of various data analysis techniques in business practices. We cover a wide spectrum of topics ranging from fundamental statistics to database, data warehouse, data visualization, and data mining, with a special focus on predictive analysis. Being an introductory course, our approach is “shallow and wide”, emphasizing on giving students a complete view of the data analytics profession, covering as many different sub-areas as time allows while not diving too deep into any one specific domain. The goal is to serve as a “guided tour” for students to gain knowledge about the different sub-areas of data analytics and understanding of which area is a best fit for their personal developments. More in-depth materials and discussion for each sub-area will be provided upon students’ requests. Course topics include the rudiments of probability and random variables, and visualization, data warehousing and OLAP analysis, dashboard, scorecard, data mining algorithms, optimization techniques, DSS and knowledge systems.