Turning Data into Action: The Path to Successful Data Governance
summary
Fragmented systems become a reproducible governance pipeline over 8 months: a VM playground, ETL pipelines into a mini data warehouse on PostgreSQL and open source tools, a data catalog that classifies domains, owners and sensitivity, and BI integration so analysts reuse datasets as products. Roles are defined (data owner, steward, architect, analyst) with RACI for processes like data access; sensitivity labels drive role-based access. Implementation is working in a test environment while teams evaluate moving to production.
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chapters (11)
- 0:00Data governance journey intro
- 1:50Why governance became necessary
- 3:17Six-step governance approach
- 5:23Priorities: quick wins vs long-term goals
- 6:47Choosing impactful use cases
- 7:48Technical foundation for governance
- 9:15Roles and responsibilities
- 10:41Mapping processes to roles
- 12:09Security versus smart access
- 13:35Journey summary and next steps
- 14:40Key takeaways
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