Feature Stores & Platforms — Week 1 CheckWeek 1 of Data Engineering for ML & AI: the feature-platform canon — DoorDash's arc, Airbnb's Chronon, LinkedIn's Feathr.

What core problem made every large shop (DoorDash, Airbnb, LinkedIn, Uber) converge on a feature platform?

Train/serve skew is the defining correctness bug of feature engineering. Its mechanism:

Point-in-time correctness in training-set generation prevents:

DoorDash cut feature-store serving costs 75% by moving the store to a different backend. The general lesson:

Stripe adapted Airbnb's open-sourced Chronon rather than building from scratch. What does a framework like Chronon actually provide?

'MLOps is mostly data engineering.' The evidence from the platform arcs: