Data governance and quality

on YouTube ↗30m

" summary

Defines a pragmatic data governance path: start with a data asset inventory and label PII, apply policies (GDPR where relevant), and score use cases with a value vs complexity matrix to pick quick wins. Gives operational rules: schedule pipelines (example: Sunday 9:00am delivery with a 24-hour SLA), monitor availability to avoid month‑long delays and pipeline interruptions. Demonstrates simple analytics like RFM cohort analysis and shows cohorts falling to ~25% retention after a year.

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" chapters (10)

1. 0:00Introduction
2. 5:09Why data governance matters
3. 9:54Data governance basics
4. 14:48Key pillars of governance
5. 16:15Aligning strategy with goals
6. 17:43Prioritizing quick wins
7. 23:35Measuring data quality
8. 26:11Pitfalls in data presentation
9. 27:32Retention insights with analytics
10. 29:24Closing and call to continue learning