In this course, you will learn to identify, evaluate, and capture business analytic opportunities that create value. Toward this end, you will learn basic analytic methods and analyze case studies on leading organizations that successfully deployed these techniques. In the first part of the course, we focus on how to use data to develop insights and predictive capabilities using machine learning, data mining and forecasting techniques. In the second part, we focus on the use of optimization to support decision-making in the presence of a large number of alternatives and business constraints. Finally, throughout the course, we explore the challenges that can arise in implementing analytical approaches within an organization.
The course emphasizes that business analytics is not a theoretical discipline: these techniques are only interesting and important to the extent that they can be used to provide real insights and improve the speed, reliability, and quality of decisions.
The concepts learned in this class should help you identify opportunities in which business analytics can be used to improve performance and support important decisions. It should make you alert to the ways that analytics can be used – and misused—within an organization.
We have three goals in this course. The first is to help you think critically about data and the analyses based on those data – whether conducted by you or someone else. The second is to enable you to identify opportunities for creating value using business analytics. The third is to help you estimate the value created using business analytics to address an opportunity.
Business analytics is an integral part of modern management – this course should provide you with the foundation you need to understand and apply these methods to drive value.
Philip H. Geier Jr. Associate Professor of Business
Omar Besbes is an Associate Professor in the Decision, Risk, and Operations division at the Graduate School of Business, Columbia University.
His primary research interests are in the are of data-driven decision-making with a focus on applications in e-commerce, pricing, and revenue management, online advertising, operations management, and service systems. His research has been recognized by the 2012 INFORMS Revenue Management and Pricing...