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Governance on autopilot, minus the turbulence
Google Cloud's Governance Agent project automates data governance by using column-level lineage to propagate metadata from upstream sources to downstream views. It shifts the process from reactive auditing to proactive automation of descriptions and tags.
Why it matters
It reduces manual labor for tagging sensitive data and describing columns, allowing data stewards to focus on complex decisions rather than repetitive entries. This improves trust in downstream data and can lower cataloguing effort for large organizations.
The details
- Propagates descriptions, business glossary terms, policy tags, and data quality scores.
- Supports grounding using external documents like PDFs when lineage is unavailable.
- VodafoneThree UK Datahub estimates the approach can reduce cataloguing effort by 75%.
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In this article
Key connections
Google owns Data Lineage API
The Data Lineage API is part of the Google Cloud stack the Governance Agent is built on.
Governance Agent is built with Knowledge Catalog
The Governance Agent project is built on Google Cloud Knowledge Catalog.
Governance Agent is built with BigQuery
The Governance Agent project is built on BigQuery.
Governance Agent uses Data Lineage API
The agent traces column-level lineage via the Data Lineage API to propagate governance metadata.
Governance Agent uses Gemini
The agent triggers a Gemini-driven Knowledge Catalog Data Documentation scan to infer relationships when lineage is missing.
Governance Agent uses Vertex AI
The agent can query a document repository indexed in Vertex AI Search for grounding context.
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Governance Agent is built with Gradio
The project ships with a Gradio-based dashboard for stewards to review and approve proposed changes.
VodafoneThree uses Governance Agent
VodafoneThree UK Datahub adopted the agent (referred to in their testimonial as the Data Steward Agent) to propagate metadata across its data estate.
Radina-Paola Ivanova works at VodafoneThree
GenAI Engineer at VodafoneThree UK Datahub.
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