Databricks Introduces Governance Hub for Account-Level Data, AI, and Cost Oversight

Governance Hub provides a centralized, account-level view of data health, AI usage, and cost across an entire Databricks estate, including deployments on AWS, Azure, and GCP. It offers prioritized recommendations and high-level KPIs with detailed drill-downs, designed to help platform and governance teams assess and act on governance health.

The Data page in Governance Hub allows users to quickly view asset inventory, including tagging, ownership, and classification coverage. It facilitates drill-downs to identify tables and schemas missing required tags or descriptions and helps manage governed tags by creating policies, editing values, and granting permissions.

Access Insights offers a principal-centric view, enabling users to see everything a specific user, group, or service principal can access across the account. This includes direct grants, inherited group membership access, and owned objects, allowing for quick debugging of access issues and auditing.

The AI vertical provides detailed observability into traffic flowing through the Unity AI Gateway, tracking token consumption, model activity, per-user spend, and guardrail coverage. It helps organizations understand AI adoption, identify which models are most active, and monitor AI budgets.

The Cost page offers a view of 30-day spend, month-to-date, and daily averages, with comparisons to prior periods. A key feature is the ability to surface untagged resources and their associated spend, making invisible costs visible for chargeback and budgeting processes.

Governance Hub integrates with Genie, allowing users to ask natural language questions about cost spikes or sensitive data lacking masking policies and receive answers and recommendations. Future capabilities will enable Genie to take autonomous actions such as configuring policies, setting alerts, and implementing recommendations.