Feature Stores for MLOps with Mike Del Balso

EPISODE 420
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About this Episode

Today we're joined by Mike del Balso, co-Founder and CEO of Tecton. Mike, who you might remember from our last conversation on the podcast, was a foundational member of the Uber team that created their ML platform, Michelangelo. Since his departure from the company in 2018, he has been busy building up Tecton, and their enterprise feature store. In our conversation, Mike walks us through why he chose to focus on the feature store aspects of the machine learning platform, the journey, personal and otherwise, to operationalizing machine learning, and the capabilities that more mature platforms teams tend to look for or need to build. We also explore the differences between standalone components and feature stores, if organizations are taking their existing databases and building feature stores with them, and what a dynamic, always available feature store looks like in deployment. Finally, we explore what sets Tecton apart from other vendors in this space, including enterprise cloud providers who are throwing their hat in the ring.
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Thanks to our sponsor Tecton

Tecton’s mission is to make world-class ML accessible to every company. Tecton enables data scientists to turn raw data into production-ready features, the predictive signals that feed ML models. The founders created the Uber Michelangelo ML platform, and the team has extensive experience building data systems for industry leaders like Google, Facebook, Airbnb and Uber. Tecton is backed by Andreessen Horowitz and Sequoia. The company is headquartered in San Francisco with an office in New York.
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