​Data science at Dun & Bradstreet: Reducing risk, increasing sales

A prominent data scientist explains how he separates signal from noise to produce meaningful business results from large data sets.
Written by Michael Krigsman, Contributor

Although data and analytics are core parts of modern computing, the underlying data science is often a black box. To shed light on this topic, I conducted a CXOTALK conversation with Anthony Scriffignano, Chief Data Scientist at Dun & Bradstreet.

Dun & Bradstreet uses data to help its customers reduce risk, market products, and increase sales. Founded before the Civil War, the company has been in the data and analysis business for about 175 years. As Chief Data Scientist, Anthony Scriffignano continues that tradition using modern tools and techniques to find meaningful information from large sets of raw data.

In the video, Scriffignano explains data science in business terms, using specific examples that highlight the challenges associated with making sense of large data sets. He also describes the difference between big data and smart data.

To read a complete transcript, click over to the episode page for this show. Watch more CXOTALK shows, to learn from real-world stories of innovation, leadership, and disruption in the enterprise.

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