Don’t Let Your Data Science Models Die A Lonely PowerPoint Death (Ep. 9)

November 15, 2016 Jeff Kelly


PowerPoint is a great presentation tool, but it is also the final resting place for many data science initiatives. “PowerPoint,” says Kaushik Das, “is where models go to die.” If you’re a data scientist, you know what he’s talking about. Das, who heads the data science practice at Pivotal, argues operationalizing predictive models in applications and business logic is the keys to saving data science models from this grim fate.

In this episode of Pivotal Insights, host Jeff Kelly and Das talk about why operationalizing data science models is so important and why so many enterprises struggle to do so. Turns out, technology is only part of the issue. Das provides tips on how to reframe the approach to data science in order to industrialize the process of getting insights to the right people at the right time on an ongoing basis.

Show Notes

About the Author

Jeff Kelly

Jeff Kelly is a Director of Partner Marketing at Pivotal Software. Prior to joining Pivotal, Jeff was the lead industry analyst covering Big Data analytics at Wikibon. Before that, Jeff covered enterprise software as a reporter and editor at TechTarget. He received his B.A. in American studies from Providence College and his M.A. in journalism from Northeastern University.

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