Shift Data Quality Left with Data Mesh Principles
summary
A central data lake in a large Indian BFSI organization misses source downtime and causes six months to debug a credit‑card onboarding metric, exposing that centralized teams lack domain rules. The claim: applying Data Mesh — domain ownership, data as a product, a self‑serve platform and federated computational governance — plus tools like Great Expectations, Monte Carlo, Apache Atlas and Synthetic Data Vault, produces discoverable SLOs, automated quality checks and a chain of trust that surfaces freshness, completeness and bias issues earlier and reduces downstream firefighting.
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chapters (7)
- 0:00Introduction and story
- 10:37Data quality problem explained
- 29:08Data quality tenets and ROI
- 37:14Data mesh principles overview
- 46:22Data as product and trust
- 57:02Self-serve platform capabilities
- 1:00:12Shifting data quality left
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