From Data Swamp to Data Symphony: Orchestrating Governance, AI and APIs
summary
Describes migrating a messy ecosystem of 30–50 data sources into governed, trusted pipelines where APIs are messengers and data quality precedes AI; claims 95% of AI projects fail without foundations, illustrates failures with a customer towing case, and proposes concrete fixes: governance frameworks, policy collaboration across legal/risk/tech, a governance persona to change culture, and treating datasets as products (dashboards, models, APIs) so models become reliable production outcomes.
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chapters (14)
- 0:00Data governance and APIs
- 1:45Governance critical for AI
- 3:54APIs backbone of data
- 5:20Data swamps reality
- 7:06Governance unlocks value
- 9:15Governance conductor
- 10:39AI soloist
- 12:45AI fun vs production
- 14:32Ethical AI governance
- 16:40Who defines policies
- 18:25Engaging governance
- 20:29Breaking data silos
- 22:16Data product mindset
- 24:24Q&A
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