Business Analytics: Identifying and Capturing Value Through Data

Jun 7–11, 2021 $4,950 (Live Online)
Questions? Contact Us:
Alberto O. Cruz
Director, Learning Solutions
+1 212-854-6037
[email protected]

Format: Five consecutive days with live sessions from 8:30 a.m. to 1:30 p.m. ET.
View the live online schedule.
Certificate Credits: 3
Learn more.
Preferred pricing is available for groups of two or more. To inquire, email [email protected].

"Business analytics is an integral part of modern management. This program will provide you with best practices and tools to identify value capture as well as understand and apply state-of-the art methods to drive value."
The program's Faculty Director Omar Besbes, Associate Professor of Business at Columbia Business School

Business Analytics: Identifying and Capturing Value Through Data

Faculty Co-Director Omar Besbes, Professor of Business at Columbia Business School

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.


Please Contact Us

Please contact our Learning Solutions Specialists at +1 212-854-3395 for a personal conversation to learn more.


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.

Upon completion of this program, you will earn three credits towards a certificate with select alumni and tuition benefits. Learn more.


PLEASE NOTE: The upcoming iteration of this program will take place in a live, virtual setting. See the agenda. You may also view the in-person program schedule for when our in-person programming resumes.

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

Part 1: Predictive Analytics

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

  1. Predict outcomes
  2. Assess the quality of our predictions
  3. Quantify the economic trade-offs that result

Part 2: Prescriptive Analytics

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

  1. Leverage the data already collected
  2. Simulate the future to quantify today’s trade-offs
  3. 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.

Part 3: The Analytic lifecycle

In the third part, we will discuss the analytic lifecycle, including:

  1. Diagnosing inefficiencies
  2. Identifying the appropriate analytical approach
  3. Deploying a decision-support system


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

Columbia Business School alumni and up to four of their colleagues are eligible for a 25 percent tuition benefit for this program. More on the Alumni Tuition Benefit.

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

Typical Participant Mix

Geographic Spread

Years of Management Experience

Job Function



Hear from Past Participant:



Omar Besbes, Faculty Co-Director
Vikram S. Pandit Professor of Business
Decision, Risk, and Operations Division, Columbia Business School


Omar Besbes is an associate professor in the Decision, Risk & Operations division at Columbia Business School.

His primary research interests are in the area 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 Section prize as well as the 2013 M&SOM best paper award. He serves on the editorial boards of the flagship journals of the discipline, Management Science and Operations Research.

He has taught core MBA courses in Operations Management and Business Analytics, an MBA elective on advanced business analytics, as well as various PhD seminars on stochastic models, revenue management, and data-driven decision making. He is a recipient of the Dean's award for teaching excellence in the core at Columbia Business School.

Besbes is a graduate of Ecole Polytechnique in France and received a MSc from Stanford University in 2000 and a PhD from Columbia University in 2008. Before joining Columbia, he was on the faculty at the Wharton School, University of Pennsylvania.


Daniel Guetta, Faculty Co-Director
Associate Professor of Professional Practice
Decision, Risk, and Operations Division, Columbia Business School


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 in business analytics, including data science, pricing, and supply chain management. Prior to joining Columbia, he was a deployed computational engineer and engagement manager at Palantir Technologies, where he worked with clients in from a wide array of industries ranging from finance to pharmaceuticals, helping them solve their business challenges by leveraging data. He completed his undergraduate studies in Physics and Mathematics at the University of Cambridge and MIT, and holds a PhD in Operations Research from the Columbia Business School.


Along with Professor Besbes and Daniel Guetta, additional Columbia Business School faculty contribute to and teach in the program.


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