Data Privacy & Compliance in a integrated Hybrid Cloud Environment
summary
Argues that GDPR-ready AI needs an information architecture and an IBM-style platform that catalogs data, records enterprise catalog and lineage, and lets analytics run where data lives across hybrid clouds; cites a 94% multi‑cloud footprint and promotes the AI Ladder (organize → analyze → infuse) as a stepwise approach. Claims tools enable visibility, traceability and auditability of automated decisions, while responsibility for unethical or illegal uploads stays with customers and vendors add an ethical-filter layer to models. Focus is on business‑case prioritization: increase revenue, avoid fines, or cut costs.
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chapters (11)
- 0:00Data privacy & compliance intro
- 1:11Regulatory challenges with new tech
- 2:58Information architecture importance
- 4:43AI compliance step-by-step
- 6:47IBM’s AI Ladder for compliance
- 9:16Hybrid cloud data management
- 11:40Multi-cloud environments
- 13:05Business-driven compliance projects
- 15:09Data governance platform
- 17:57Holistic data strategy
- 18:39Q&A on ethical AI
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