Efficiency up, failed releases down; compliant production data for your test and dev environments
summary
Explains how to get realistic, compliant non‑production databases by tagging sensitive fields with Data Catalog, generating rules to detect PII and formats, and applying deterministic and substitution masks with Data Masker so emails, cards and linked rows remain realistic but safe. Creates one anonymized source image and spawns space‑efficient clones (supports very large DBs, demo mentions ~64 TB) to cut per‑developer restore time from many hours to minutes. Notes generated fake data often mismatches production distributions.
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chapters (14)
- 0:00Compliant production data intro
- 3:19Why production data is risky
- 6:55Realistic test data role
- 9:05Identifying and cleaning data challenges
- 12:42Data management hurdles
- 18:27Tagging data for compliance
- 26:12Never use production data directly
- 27:14Generated vs masked data
- 30:06Large DBs in development
- 32:37DB sharing limits
- 35:44Risks of unmasked data
- 38:40Catalog and masking tools
- 40:46Demo: Masking and cloning DBs
- 47:14Summary and Q&A
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