Analytics I Visual And Predictive Techniques

AY2015/2016 Semester 1

Learning Objective Most organizations are data rich and information poor. The large volumes of data potentially could reveal useful information in most business contexts. Business Analytics involves the art of exploring and analyzing large quantities of observational data in order to discover meaningful patterns and useful information to support decision makings. The primary objective of this course is to introduce participants to various techniques available to extract useful information from the large volumes of data an organization might possess. At the end of the semester, participants will not only appreciate the substantial opportunities that exist in the business intelligence realm, but also learn techniques that will allow them to exploit these opportunities. The course will cover general concepts in the business analytics field, along with many popular techniques like decision trees and clustering. The focus will be on how the techniques are to be used, and the details of the methodologies will be covered only to the extent necessary to understand when and how each technique can be used. Students will also gain experience using data mining software. We will focus on the use of SPSS, which is a popular package for various industries. Content This course introduces Business Analytics at an introduction level. Main contents include: data preparation, data visualization, data dimension reduction, some basic models in unsupervised learning and supervised learning.