Introduction to Data Mining

Catalog description

The "business intelligence" wave has quickly spread throughout the business sector. This wave begins with canned reports, through query & reporting, data warehouse/marts, online analytical processing (OLAP), then to data mining. This course discusses how data mining techniques are used to transform large quantities of data into information to support tactical and strategic business decisions. While the student will be introduced to data mining techniques, the focus of the course is learning when and how to apply data cleaning, appropriate methodology, and more importantly read and process output meaningfully in business applications and explain the output clearly and concisely without analytics jargon. The aim of this course is to provide the student with the foundation to data mine and understanding of the data mining process. It includes an introduction to some advanced statistical decision-making tools, including several multivariate data mining techniques, factor/principal component analysis, cluster analysis, ANOVA, multivariate regression, and logistic regression.