Data Observability in 10 Minutes


Data Observability (DO) is an emerging category that helps data teams identify, resolve, and prevent data quality issues by continuously monitoring the state of their data over time.

This demo is a deep dive into Metaplane, the only engineer-first, self-serve data observability platform. Data teams at high-growth companies (like Vendr, Reforge, Weedmaps, Teachable, SpotOn, etc) use Metaplane to save engineering time and increase trust in data by understanding when things break, what went wrong, and how to fix it — before the CMO messages them about a broken dashboard.

By the end of the demo, you’ll know how to setup out-of-the-box and custom tests, automatically extract lineage throughout your data stack, and triage data quality alerts with your team.


Kevin Hu is co-founder and CEO of Metaplane, a data observability company based in Boston focused on helping every team find and fix data quality problems with as little setup as possible. Metaplane is backed by leading investors including Y Combinator and the founders of Okta, HubSpot, and Lookout, and is used across high-growth teams and large enterprises.

Kevin has over a decade of experience working in data. Most recently, he researched the intersection of machine learning and data science at MIT, where he collaborated with Fortune 500 companies while earning his PhD, SM, and SB. His research has been published in top computer science venues like ACM CHI, KDD, and SIGMOD, and featured in the New York Times, Wired, and The Economist.

Open Data Science




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