Data Observability for Machine Learning Teams

apply(conf) - May '22 - 10 minutes

Once models go to production, observability becomes key to ensuring reliable performance over time. But what’s the difference between “ML Observability” and “Data Observability”, and how can ML Engineering teams apply them to maintain model performance? Get fast, practical answers in this lightning talk by Uber’s former leader of data operations tooling, and founder of data observability company, Bigeye.


Kyle Kirwan

CEO & Co-founder

Bigeye

Kyle Kirwan is the cofounder and CEO of Bigeye, a data observability platform. Before starting Bigeye, he was a Data Product Manager at Uber where he led the development of internal data operations tools that enabled data discovery, lineage, freshness, observability, and incident management for hundreds of data engineers, analysts, and scientists within the company. He lives in New York City with his fiancé and prefers Cherry MX Blue keyboard switches.