BUA 682 - Data Pre-Processing for Business Analytics

This course is designed to enhance student’s understanding of data quality problems commonly encountered in business environments including but not limited to missing data, noisy data, and data biases. This course discusses mechanisms of these problems and their impact on data analysis and modeling results and presents how to solve these problems by using different data pre-processing techniques such as imputation, integration, normalization, and transformation. Students practice these techniques with business data sets using mainstream analytical software.

Prerequisites & Notes
BUA 680 or equivalent, or permission from Graduate School of Business.

Credits: 3