Why You Need Unity Catalog for Your Data Lakehouse

Dive into the world of data governance with our comprehensive guide on the Unity Catalog in Databricks. Discover how to refine your data control with advanced features like Row Level Security, column-level masking, and much more.

🔍 What You'll Learn:

* Implementing Row Level Security for tailored data access.
* Utilizing Column Level Masking to protect sensitive information.
* Leveraging Managed Data Sources & External Locations for organized data storage.
* Applying Default Access Controls to enhance security by catalog or schema.
* Automating Lineage for all your workloads to track data usage seamlessly.
* Integrating Built-in Search and Discovery to swiftly locate data assets.
* Exploring Delta Sharing for secure, cross-organization data sharing.

📚 Additional Resources:

Databricks Documentation on Unity Catalog
Best Practices for Data Governance
📝 Note: Unity Catalog provides a unified governance layer for all your data and AI assets across all Databricks workspaces, simplifying permissions management, and ensuring compliance with your data governance policies.

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#DataGovernance #Databricks #UnityCatalog #DataSecurity #BigData #DeltaSharing


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00:00 Introduction
00:39 Intro
01:35 Agenda
02:44 Row-level security and column-level Mask
05:41 Managed Data Sources and External Locati
10:45 Default Access to Storage by catalog or
12:32 Govern filesystems and Objects distinctly
14:04 Access Data from the specified environment only
16:14 Life of a Query with Unity Catalog
19:48 Automated Lineage for all Workloads
21:02 Lineage Flow -How does it work?
22:55 Built-in Search and Discovery
25:09 Discovery Tags
26:33 Delta Sharing- under the hood

[NasimaKhatun-zi]

What option i use in place of input_file_name() while using unity catalog