Introduction to Data mining, appropriate modeling and prediction in the decision-making process. Upon completion, students understand the basic concepts, gain gain deeper knowledge in analytics and perform better data analytics in a fast pace decision making environment.

This introductory course brings together the basic techniques of optimization and the statistical methods that can handle large sets of data with the appropriate software in the decision-making process commonly known as Business Analytics. Topics include data exploration, data visualization, predictive modelling techniques

Most of the business schools nationwide have started programs in Business Analytics, or at least a minor both at the undergraduate and graduate levels to provide practical solutions to the policy makers in the context of growing data, usually described as Big Data. These required the development of courses starting from pre-requisites, core courses and electives in the last three to four years. Unfortunately, there seems to be no consensus on the contents of these courses, software and even text books among the scholars in the literature including the introductory course on the subject matter. A well-organized introductory course on the topic is essential as a foundation to the development of other courses in the curriculum ladder. The purpose of this presentation is to bring up the issues and seek input and guidance from other colleagues and participants with the hope of developing and finalizing in to about 80% standard contents like any other introductory course in business disciplines such as Accounting, Finance and Economics.

Bharat Kolluri

Affiliation

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Challenges and opportunities in curriculum development for Business Analytics

A New Look at Money Demand in the United States