Data Quality vs Everyone
summary
Discussion of why engineers should assume data is low quality by default and treat data quality as a core engineering problem. Covers how bad data undermines business decisions and product features, and argues for practices to detect, measure and enforce data quality in production systems.
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chapters (10)
- 0:00Introduction
- 1:09What is data quality
- 5:05Data quality metrics
- 9:57Checking data
- 15:36Data Quality tools
- 20:31Click Stream case study
- 27:43Team metrics and KPIs
- 34:49Auto test generation
- 39:52Key takeaways
- 41:15Q&A
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