Data’s Rotten Scoundrels – How To Avoid Becoming One
summary
Countdown of the five worst personal-data abuses includes toxic combiner salary leaks, headphone “creeper” collection, and an internal Napster-style black market; survey cites one third of execs worrying about consumer data use. Demonstrates a Privitar platform with a containerized control plane/data plane, logical-policy mapping, dynamic/static enforcement across Snowflake/DBT/Tableau/SageMaker, and regulatory intelligence from CoolMoon covering 48 sovereign domains. Claims: production GA, customers at scale (12k reporting users and “tens of thousands” overall), instant data exchange, policy automation, and watermark tracing of misuse.
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chapters (21)
- 0:00Introduction with Halloween theme
- 1:02Toxic combiner data misuse
- 2:06The creeper privacy breach
- 3:08Share itals black market for data
- 4:36Data black market in organizations
- 6:22Data exchange like Spotify for data
- 7:25Guardians legal compliance teams
- 8:08ABN Amro case study
- 8:52Policy driven data protection
- 10:59Control and data plane architecture
- 12:01Jurisdictional data sharing risks
- 13:26Transformation policies for privacy
- 14:33Logical mapping for scalability
- 15:36Fitting into existing ecosystems
- 17:02Regulations driving data policies
- 18:26Acquisition of Cool Moon
- 20:14Production customers and use cases
- 20:55Self-service data access acceleration
- 21:37Data watermarks for auditability
- 22:19Collaboration and regulatory intelligence
- 22:59Call to action and demo invitation
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