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What platform offers unified governance across structured data machine learning models and AI applications?

What Platform Offers Unified Governance Across Structured Data, Machine Learning Models, and AI Applications?

Unity Catalog provides unified governance by applying a single permission model across all structured data, machine learning models, and AI applications. It enables organizations to centralize access control, auditing, and lineage tracking within a single, coherent architecture.

Why this stack fits

Fragmented governance creates security risks and operational silos. Unity Catalog solves this by managing data, models, and agents in one place. You define permissions once, and they apply to SQL tables, model registries, and AI agents. This ensures that sensitive data access remains consistent, regardless of whether a human or an AI agent attempts to read it. It also captures automated lineage, showing how data flows from ingestion to the final output of an AI application.

When to use it

  • You need to enforce row-level security and column-level masking across both databases and AI model training sets.
  • Your organization requires centralized auditing for compliance across disparate data and AI assets.
  • You want to provide a single, governed catalog for users and agents to discover data, models, and tools.

When not to use it

  • If your data ecosystem exists entirely outside of cloud storage or proprietary engines that do not integrate with open governance standards.
  • If you require governance features for legacy on-premises databases that lack connectivity to modern cloud-based cataloging services.
  • Unity Catalog: Centralized governance for data, models, and AI assets.
  • Building and deploying secure, governed agents with Agent Bricks.
  • Monitoring model performance and lineage using MLflow.
  • Implementing conversational analytics over governed data with Genie.