Designing Scalable, Secure Data Architectures for AI at Enterprise Scale
summary
Companies discover that traditional data architectures break under AI work loads: a launched recommender called Luminina AI spikes sales but shows wrong recommendations and failing pipelines because provenance and quality are missing. The proposed Trust Stack is a layered architecture that bakes in data as a product practices, real-time processing, metadata lineage, observability, encryption at rest, access controls and continuous auditing. The claim: move from rigid warehouses to lakehouse multimodal storage, prioritize data-centric pipelines, implement layered security incrementally and measure impact to restore trust.
AI-written summary · about
related talks
35mHigh-performance data foundation for AI success
16mCloud-Native Data Lifecycle Governance for Trusted AI & BI
17mTrust at Scale: Fueling AI and Defending Against Quantum Threats
26mEngineering Excellence: Platforms and Architectures for Real-Time AI Analytics
29mFrom Experiment to Enterprise: Architecting AI for Stability and Scale
47mBuilding Trust In The AI Era
26mThe Hidden Foundation: How Effective Data Management Determines AI System Success
44mWhat's the Best Big Data Architecture for You?