Rethinking Data Catalogs: The Promise and Pitfalls
summary
Claims that catalogs are frequently under‑used and duplicated across teams with 80% of people saying catalogs miss expectations and 82% reporting adoption struggles. Examples name Snowflake Databricks Monte Carlo and show an implemented pattern: shift left, publish data contracts and SLOs linked to system catalogs, measure success by number of prioritized use cases with SLOs met and lead‑time reduction from discovery to value. A worked example (Hogwarts Financials) illustrates where integration and workflow changes make catalogs useful.
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chapters (10)
- 0:00Introduction
- 2:23Agenda
- 3:00Defining data catalogs
- 5:08Pitfalls of data catalogs
- 13:41Evaluating investment needs
- 14:40Optimizing the golden path
- 19:18Integrating into workflows
- 24:28Measuring success
- 25:35Key takeaways
- 26:51Q&A session
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