Daniel Guetta
- Associate Professor of Professional Practice
- Decision, Risk, and Operations Division
- Director
- Center for Pricing and Revenue Management and Business Analytics Initiative
- Areas of Expertise
- Artificial Intelligence (AI), Operations & Supply Chain Management
- Contact
- Office: 1132 Kravis
- E-mail: [email protected]
Daniel Guetta is Associate Professor of Professional Practice at Columbia Business School. His research focuses on the ways companies can harness the power of data and analytics to drive value. He teaches classes in business analytics, including data science, pricing, supply chain management, and technical tools such as python and cloud computing. He has authored award-winning case studies in the area with a number of companies, and co-authored "Python for MBAs". Prior to joining the faculty at Columbia, he was a data scientist and engagement manager at Palantir Technologies, where he worked with clients around the world in fields ranging from finance to pharmaceuticals to help them solve their hardest problems using data. He completed his undergraduate studies in physics and mathematics at Cambridge and MIT, and holds a PhD in Operations Research from Columbia Business School.
- Education
-
PhD, Columbia, 2015
- Joined CBS
- 2017
All Activities
Commitment to Excellence Awards
with Charles Guetta
Weaving AI into the Classroom
Using AI in the Classroom at Columbia Business School
Becoming Data Fluent
Python for MBAs: Improving Decision-Making in Business
'Hyper-Speed and Hyper-Scale'
Python for MBAs: Improving Decision-Making in Business
- Case ID
- 250204
Planting the Seeds of Success: Optimizing Inventory at The Sill
How does one determine the optimal limited shelf-life inventory to hold upon transformation to a fully-online business?
- Case ID
- 250201
Connecting the Dots for NYC Clean Power: The Case of NineDot Energy
What are the logistical challenges inherent in a company’s clean energy business model, using analytical techniques?
- Case ID
- 240202
The Cambridge Analytica Scandal: Psychographics, Facebook, and the 2016 US Elections
How would a firm use big data to target individuals in political and marketing messaging?
- Case ID
- 240201
BinIt: Revolutionizing the Recycling Industry with Computer Vision, AI, and Deep Learning
How can a company use computer vision and AI to optimize recycling and waste management on a broadscale?
- Case ID
- 230201
Enabling X-to-the-xth: the Operational Secret Behind Uber's Explosive Growth
How does Uber's operational business model support its tremendous growth since inception?
- Case ID
- 220205
Automating Bureaucracy with Python: The Case of the Springfield Bail Fund
How can the Springfield Bail Fund automate and track its large volume of inquiries and manage the information received in an organized manner using Python and Excel?
- Case ID
- 220204
Aroma Consumer Products Co.: Managing Capacity for a Growing Company
How can Aroma Consumer Products Co., the primary overseas manufacturer for a growing US candle producer, expand production capacity to meet a sudden demand increase?
- Case ID
- 220203
Continuous Quality Monitoring via Data and Analytics at The Estee Lauder Companies
How should Estee Lauder's analytics team respond to a spike in online complaints from its customers?
- Case ID
- 220201
Autonomous Vehicles: The Technology Behind the Magic
What predictive models can help to establish parameters for autonomous household appliances —such as robotic vacuum cleaners—and how are these models applicable to future autonomous driving vehicles?
- Case ID
- 210212
Analytics in Fixed-Income Trading
How might predictive analytics help to support the bond trading process?
- Case ID
- 210211
At the Frontier of Retail in the 21st Century: Modern Fulfillment and The Case of FlexiWeight
With a goal to revolutionize the way America exercises, can Flexiweight find the right fulfillment model to deliver on its mission?
- Case ID
- 210210
Continuous Quality Monitoring via Data and Analytics at Patina Beauty
How should Patina Beauty's analytics team respond to a spike in online complaints from its Chinese customers?
- Case ID
- 210409
Mastercard's Organizational Structure: The Making of a New AI Powerhouse
Which organizational structure would enable Mastercard to most effectively deploy its artificial intelligence expertise, with a goal to becoming an AI powerhouse?
- Case ID
- 210207
Analytics in American Football: A New Frontier
Can American football team coaches use statistical analysis to optimize their coaching strategies?
- Case ID
- 200202
From Intuition to Data-Driven Analytics: The Case of Dig
Poised for expansion, how should restaurant chain Dig harness the power of data-driven analytics to scale its value chain?
- Case ID
- 190202
An Introduction to AI for Text Mining: A Companion to the Evisort Case
What processes make artificial intelligence-driven text mining possible?
- Case ID
- 190201A
Evisort: An AI-Powered Start-up Uses Text Mining to Become Google for Contracts
Should technology start up Evisort customize its AI-enhanced contract management software for large potential clients or continue to enhance its software offering to meet its growth strategy?
- Case ID
- 180203
Supply Chain Coordination and Contracts in the Sharing Economy - a Case Study at Cargo
How should Cargo, a provider of in-car goods and services for the rideshare economy, most efficiently manage its two-sided supply chain?