RAG-Ready Patterns for Data Platforms: Making Systems Ready for Grounded Generative AI

Enterprises are under pressure to apply generative AI to their data, but most data platforms weren't designed to support retrieval-augmented generation (RAG)-based conversational systems.Built for dashboards and siloed reporting, they often lack context, structure, and governance that AI applications require.RAG-Ready Patterns for Data Platforms provides a practical blueprint for closing that gap, showing how to evolve fragmented data estates into AI-ready foundations delivering trusted insights. Drawing on real-world experience building one of Microsoft's largest data platforms, the authors present proven patterns for unifying data across silos, capturing metadata, and embedding governance.Rather than treating RAG as an application-level concern, this book reframes it as a platform capability.With clear explanations, architectural diagrams, and reusable playbooks, you'll learn to design platforms that enable developers to build scalable, retrieval-augmented AI systems grounded in ente