3-Step Path for Fixing Data Discoverability
summary
Claims that a catalog becomes useful only when it supports concrete features: searchable metadata, automated access requests, shallow snippets and masked PII, and direct jumps into compute like Databricks with templates. Mentions tools such as Data Hub, atlan and kbra, cites surveys (30% time lost, McKenzie 20%, one client 40% down to 14%) and changes a promised 3‑step path into a measurable five steps: search verify access explore govern, plus lifecycle actions like cost tracking and delete buttons.
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chapters (11)
- 0:00Data discoverability challenges
- 2:09Why discoverability matters
- 8:11Passive data catalog problems
- 11:45From passive to active metadata
- 13:11Requesting data access
- 15:18Shallow and deep data exploration
- 16:46Advanced catalog use cases
- 17:27Catalogs as data product gatekeepers
- 18:49Tracking usage and costs
- 20:37Governance and quality in catalogs
- 22:46Five-step path summary
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