About the Focus Area

Data science is at the center of informed business decision-making.

The global business landscape is increasingly data-driven. Valuable data is generated in every facet of business, and data science techniques help companies find pragmatic solutions to inform strategy, execution, and organizational leadership in finance, management, and marketing.

Data scientists recognize patterns and form insights, contribute to risk management, build models, create viable products, and present and communicate financial data to effectively support company executives in sales, product development, planning, and customer acquisition. Causal techniques, including correlation and multiple regression analysis, are used to prepare business forecasts and long-range plans. Financial analytics are used to audit and optimize financial strategies based on both company and industry data.

This nexus of data science and business analytics and Columbia’s position in the global business hub and ecosystem that is New York City places DSI in a unique position to leverage data science to improve business processes.

DSI researchers study revenue maximization problems and combine labor market data with data science methods to identify factors and environments that shape gender and racial inequality.

Teams of M.S. in data science students have developed and evaluated novel spatio-temporal trajectories clustering methods used for traffic planning, inventory optimization, and understanding movements; used public data, anomaly detection, and natural language processing to create a dashboard and pip-installable package to help executives learn the full news history of a potential client; and predicted the Moody’s rating changes.

Collaboratory courses also prepare Columbia Business School students to succeed in an increasingly data-intensive world with a curriculum focused on programming, databases, and data analytics and the latest techniques for gathering, managing, and interpreting data.

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