The document explains how retrieval-augmented generation (RAG) transforms enterprise data into generative AI. It highlights that the main challenge lies in accessing large volumes of data, moving it into centralized repositories like warehouses or lakes, and preparing it for AI use. Once stored, data can be processed into knowledge graphs or embedded as vectors in a database, enabling retrieval models to provide foundation models with contextual information for more accurate outputs. This approach allows organizations to apply generative AI to proprietary data efficiently. Fivetran supports this process by offering secure, compliant, and flexible data integration, with over 500 no-code connectors, change data capture, and platform extensibility. The company ensures compliance with standard

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