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Columbia Business School

Business Analytics: Identifying and Capturing Value Through Data

Available dates

Sep 14—16, 2020
3 days
New York, New York, United States
USD 6450
USD 2150 per day


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About the course

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. In addition, many current and recent startups such as Palantir and Splunk are based on the application of analytics to large data bases. 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 three-day program, executives learn to identify, evaluate, and capture business analytic opportunities that create value. Learn how to use data to develop insights and predictive capabilities using machine learning, data mining, and forecasting techniques. Next, find out how the use of optimization can support decision-making in the presence of a large number of alternatives and business constraints. Finally, explore the challenges that can arise in implementing analytical approaches within an organization.


The program emphasizes that business analytics can provide real business insights and improve the speed, reliability, and quality of your business decisions. The concepts learned will help you identify opportunities in which business analytics can be used to improve performance and will make you alert to the ways that analytics can be used – and misused – within an organization.

Attending this program will:

  • Help you think critically about data and the analyses based on those data — whether conducted by you or someone else
  • Expose you to many different applications of business analytics across industries and sectors
  • Enable you to identify opportunities for creating value using business analytics
  • Empower you to estimate the value created using business analytics to address an opportunity

You'll receive access to leading research, best practices, and thought leadership from our university which has ranked among the top universities for its research in analytics-related areas.

Program Structure

The program is organized around three days, taking participants through several key topics and applications.

Day 1: Predictive Analytics

On day one, we will cover applications in consumer lending, recommendation systems, healthcare analytics, financial analytics, and sport analytics, which will allow you to:

  • Predict outcomes
  • Assess the quality of our predictions
  • Quantify the economic trade-offs that result

Day 2: Prescriptive Analytics

On the second day of the program, we will discuss different frameworks to support decision-making in organizations, which allow you to:

  • Leverage the data already collected
  • Simulate the future to quantify today’s trade-offs
  • Optimize millions of decisions in conjunction with thousands of business and physical constraints
  • We will cover applications in retail, insurance, pharmaceutical detailing, and financial analytics among others.

Day 3: The Analytic lifecycle

On the third day, we will discuss the analytic lifecycle, including:

  • Diagnosing inefficiencies
  • Identifying the appropriate analytical approach
  • Deploying a decision-support system

Who should attend

The program is designed for managers and team leaders looking to gain a better understanding of how to leverage data to drive business results.

It is ideal for, although not limited to, executives working in the following industries:

  • Consulting whose backgrounds include strategy, strategic planning, or process optimization
  • Consumer products, including cosmetics and luxury goods, and manufacturing
  • Finance and financial services
  • Healthcare and pharmaceuticals
  • Insurance
  • Publishing, television and entertainment

Executives from the following companies have attended this program:

  • Bristol Myers Squibb
  • Citi
  • Daiichi-Sankyo Inc.
  • Deloitte Consulting
  • FOX Sports
  • Land O'Lakes
  • Macy's, Inc.
  • McKinsey & Company
  • New York Power Authority
  • The Estee Lauder Companies Inc.
  • Viacom
  • Zoetis

Trust the experts

Omar Besbes

Biography 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 m...


Daniel Guetta

Daniel Guetta is the director of the Business Analytics Initiative, jointly led by the Columbia Business School and Fu Foundation School of Engineering and Applied Science. He is also a lecturer in the Discipline of Decisions, Risk, and Operations at Columbia Business School. He teaches classes i...


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