Business analytics refers to the ways in which enterprises such as businesses, non-profits, and governments can use data to gain insights and make better decisions. Business analytics is applied in operations, marketing, finance, and strategic planning among other functions. The ability to use data effectively to drive rapid, precise and profitable decisions has been a critical strategic advantage for companies as diverse as WalMart, Google, Capital One, and Disney; besides driving startups such as Palantir and Splunk. With the increasing availability of broad and deep sources of information — so-called “Big Data” — business analytics are becoming an even more critical capability for enterprises of all types and all sizes.
In this course, students learn to identify, evaluate, and capture business analytic opportunities that create value. The course covers basic analytic methods and analyzes case studies on 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: The concepts learned in this class should help students identify opportunities in which business analytics can be used to improve performance and reliably support important decisions in the real world.
Sidney Taurel Associate Professor of Business
Yash Kanoria is the Sidney Taurel Associate Professor of Business in the Decision, Risk and Operations division at Columbia Business School, working primarily on matching markets and the design and operations of marketplaces. Previously, he obtained a BTech from IIT Bombay in 2007, a PhD in Electrical Engineering from Stanford in 2012, and spent a year at Microsoft Research New England during 2012-13 as a ...