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Metric Semantic Layer: How Lyft Governs and Scales Key Data Definitions
Lyft implemented a Metric Semantic Layer to stop 'metric drift' by enforcing standardized business logic across all company data products.
What: The platform introduces 'Golden Metrics' with dual ownership between business and operational teams, accessible via Python APIs, Amundsen, and AI agents.
Why it matters: Governing definitions via code, rather than just documentation, is becoming a prerequisite for using AI agents on internal data without hallucinations.
Original article
Lyft built an internal Metric Semantic Layer to solve metric definition drift and ensure consistent business logic across teams. It enforces governance through “Golden Metrics,” dual ownership (Business + Operational owners), versioned updates, and access via Python APIs, self-service UI, Amundsen catalog, and AI agents, providing a single source of truth that propagates changes automatically.
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