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Explaining data and AI platform architecture patterns and building blocks

Explains where data, compute and permissions live in common data and AI architectures (warehouse, lakehouse, data mesh, batch and streaming, event-driven, retrieval-augmented generation, managed versus self-hosted) and states which quality attributes, cost drivers and lock-in each pattern favours.