Google’s Agentic Data Cloud targets enterprise AI bottlenecks

Google’s data tooling is positioned as groundwork for enterprise AI, with Knowledge Catalog organizing corporate information and Agentic Data Cloud connecting data across environments.

Enterprise AI strategies depend on clean, reliable data, making data control a prerequisite for moving generative AI from experiments into scaled operations. Google’s Knowledge Catalog, formerly Dataplex, uses Gemini to structure, map, catalog, and clean corporate knowledge so organizations can identify where information lives and create a single view of their data estate.

Agentic Data Cloud extends that foundation by allowing companies to access and analyze information across clouds, third-party platforms, formats, and repositories without moving it into a centralized system. Its Zero-ETL approach is designed to reduce manual ingestion, break down multi-cloud silos, extract insights from distributed sources, and apply unified security standards to data access.

The practical business case centers on lowering vendor lock-in, speeding data preparation, and giving enterprises a stronger base for building agents through the Gemini Enterprise Agent Platform. By improving data availability, quality, and sovereignty, these tools aim to address one of the main barriers to deploying AI systems that support real business goals.

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