Engineering Trust in Data
summary
Argues that trust in data is solved by an engineering-led, continuous improvement methodology rather than vague strategy, citing 15 years of delivery and three case studies delivering billions in combined value. Recommends concrete patterns: tech-agnostic pipelines, operational rigor, instrumentation and SLAs, lifecycle and governance, training, and security—notes the most common failure is simple disk-full outages. Pushes open standards for external sharing like verifiable credentials / distributed identity and treats ISO 27001 as operational discipline, not a silver bullet.
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chapters (10)
- 0:00Introduction
- 2:40Engineering Trust in Data
- 4:58Data Plumbing
- 13:37Building Trust in Data
- 16:52Continuous Improvement Cycle
- 17:23Data Acquisition
- 23:09External Trust
- 25:04Building Trust
- 26:12International Data Sharing
- 26:39Questions
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