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learn-pr/wwl-databricks/govern-unity-catalog-objects/includes/1-introduction.md

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Effective data governance requires more than just controlling access—it demands visibility into your data assets, accountability for how they're used, and enforcement mechanisms that scale with your organization. As data platforms grow in complexity, managing table definitions, tracking data lineage, enforcing retention policies, and sharing data securely become increasingly challenging. **Unity Catalog** in Azure Databricks provides the foundation for comprehensive governance that addresses these challenges through centralized metadata management and policy enforcement.
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When you govern Unity Catalog objects, you work across several interconnected capabilities. You document tables and columns with **comments and tags** that help data consumers discover and understand your assets. You implement **attribute-based access control (ABAC)** using governed tags and policies that automatically enforce fine-grained permissions. You apply **row filtering and column masking** to protect sensitive data while maintaining query functionality. You configure **data retention policies** using Delta Lake's VACUUM and predictive optimization to manage storage costs and meet compliance requirements.
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When you govern Unity Catalog objects, you work across several interconnected capabilities. You document tables and columns with **comments and tags** that help data consumers discover and understand your assets. You implement **attribute-based access control (ABAC)** using governed tags and policies that automatically enforce fine-grained permissions. You apply **row filtering and column masking** to protect sensitive data while maintaining query functionality. You configure **data retention policies** using Delta Lake's `VACUUM` and predictive optimization to manage storage costs and meet compliance requirements.
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Beyond access control, governance extends to **data lineage tracking** that shows how data flows through your pipelines, enabling impact analysis and troubleshooting. **Audit logging** captures who did what and when, supporting security investigations and regulatory compliance. For external collaboration, **Delta Sharing** lets you share data with partners and customers while maintaining governance controls over what they can access.
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learn-pr/wwl-databricks/govern-unity-catalog-objects/includes/3-configure-attribute-based-access-control-tags-policies.md

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| Aspect | Standard tags | Governed tags |
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| ---------------- | --------------------------------- | ---------------------------------- |
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| Scope | Any key-value pair | Predefined keys and allowed values |
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| Control | Any user with APPLY TAG privilege | Only users with ASSIGN permission |
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| Control | Any user with `APPLY TAG` privilege | Only users with `ASSIGN` permission |
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| Purpose | Organization and discovery | Policy enforcement and compliance |
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| Visual indicator | None | Lock icon in Catalog Explorer |
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learn-pr/wwl-databricks/govern-unity-catalog-objects/includes/5-apply-data-retention-policies.md

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Every organization faces the challenge of balancing data availability with compliance requirements and storage costs. When you implement **data retention policies** in Azure Databricks, you ensure that data is kept only as long as necessary while remaining accessible for legitimate business needs. This becomes especially critical when regulations require you to delete personal data upon request.
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In this unit, you learn how to configure retention settings, use **VACUUM** to remove obsolete data, handle deletion requests for compliance, and automate maintenance with **predictive optimization**.
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In this unit, you learn how to configure retention settings, use **`VACUUM`** to remove obsolete data, handle deletion requests for compliance, and automate maintenance with **predictive optimization**.
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## Configure Delta Lake retention settings
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