Donghan Zhang

Commercial experimentation platforms promise everything – feature flags, metrics, and analysis, but often limit flexibility when you want to go beyond the basics. At Databricks, we took a different approach: we built our own full-stack experimentation platform entirely on our internal Databricks and used it to power hundreds of product releases every month. In this talk, we’ll show how you can do the same. You’ll learn how we: - Use Unity Catalog to centralize and govern feature enablement data - Define reusable, trustworthy metrics with our internal Metrics Platform - Run scalable experiment analyses with Lakeflow Serverless Jobs - Deliver fast, intuitive user experiences with Lakehouse Apps Beyond the platform itself, we’ll share how we extend it with advanced methodologies that go far beyond what commercial tools support. Whether you’re a data scientist or platform engineer, you’ll walk away with a blueprint for building a reliable, extensible, and fully owned experimentation platform on Databricks.

Join us as we unveil how we transformed the largest Databricks workspace into the best-in-class lakehouse through Unity Catalog. Discover how we harnessed lineage and unified access management to build ultimate governance automation.