Quality Platforms — Week 1 CheckWeek 1 of Data Quality, Contracts & Observability: the platform arcs at Airbnb, Uber, Twitter, and Criteo. Every question traces to a case study you read this week.

Airbnb ran Midas certification for years, then ADDED the automated Data Quality Score. What problem did the score solve that certification couldn't?

In Airbnb's Wall framework, what's the operational difference between a blocking and a non-blocking check?

Uber's UDQ runs ~100,000 tests a day over 2,000+ critical datasets without teams hand-writing most of them. Where do the tests come from?

UDQ evaluates ITSELF using precision and recall on incidents. Why does that matter for a quality platform?

Which THREE mechanisms does Uber use against alert fatigue?

Twitter's DQP lands every check result in BigQuery rather than only firing alerts. What does that design enable?

What incident forced Criteo to build DataDoc's lineage capability?

Airbnb's deepest scaling lesson — 'enforcement doesn't scale, but X does.' What is X?