Machine learning for operational analytics and business intelligence

The O’Reilly Data Show Podcast: Peter Bailis on data management, ML benchmarks, and building next-gen tools for analysts.

By Ben Lorica
October 10, 2019
Machine learning for operational analytics and business intelligence

Machine learning for operational analytics and business intelligence
Data Show Podcast

 
 
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In this episode of the Data Show, I speak with Peter Bailis, founder and CEO of Sisu, a startup that is using machine learning to improve operational analytics. Bailis is also an assistant professor of computer science at Stanford University, where he conducts research into data-intensive systems and where he is co-founder of the DAWN Lab.

We had a great conversation spanning many topics, including:

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  • His personal blog, which contains some of the best explainers on emerging topics in data management and distributed systems.
  • The role of machine learning in operational analytics and business intelligence.
  • Machine learning benchmarks—specifically two recent ML initiatives that he’s been involved with: DAWNBench and MLPerf.
  • Trends in data management and in tools for machine learning development, governance, and operations.

Related resources:

Post topics: AI & ML, Data, O'Reilly Data Show Podcast
Post tags: Podcast
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