What is the Databricks Unity Catalog?

The Databricks Unity Catalog is a unified governance solution designed for managing data and AI assets within the Databricks Lakehouse Platform.

It offers a centralized platform that enables organizations to efficiently manage, audit, and secure their data assets across different cloud environments. This unified approach ensures robust data governance and compliance, enhancing the overall integrity and security of data operations.

Why should we use the Databricks Unity Catalog?

The Databricks Unity Catalog offers several compelling reasons for its adoption, making it an essential tool for organizations looking to enhance their data governance and management capabilities. Here are the key benefits:

Centralized metadata management  

The Unity Catalog provides a central location to manage metadata for all data assets, including tables, views, and machine learning models. This centralized approach simplifies metadata management, ensuring consistency and ease of access across the organization.

Fine-grained access control  

The Unity Catalog allows for detailed access controls at the table, row, and column levels. This granularity ensures that only authorized users can access specific data, enhancing security.

It enables data masking and row-level security for sensitive data, protecting confidential information from unauthorized access.

These features ensure that data is accessed securely and in compliance with organizational requirements, maintaining data integrity and privacy.

Data lineage  

The Unity Catalog tracks the data flow from source to destination, providing transparency and traceability for data transformations and usage. This visibility is crucial for understanding data dependencies and ensuring data accuracy.

It assists in impact analysis, debugging, and compliance reporting, making it easier to identify and resolve issues, as well as to meet regulatory requirements.

Integration with BI tools 

The Unity Catalog seamlessly integrates with popular BI tools like Power BI and Tableau, facilitating easy data consumption and analysis. This integration enables users to leverage their preferred BI tools while benefiting from the robust data governance provided by the Unity Catalog.

By leveraging the Databricks Unity Catalog, organizations can achieve a higher level of data governance, security, and compliance, ultimately enhancing their data management capabilities and driving better business outcomes.

What is an example of a use case?  

Scenario 

A financial services company, FinCorp, manages large volumes of sensitive data, including customer information, transaction records, and financial reports. Ensuring data privacy, security, and compliance with regulations like GDPR and CCPA is crucial. FinCorp also needs to streamline data access for analysts, data scientists, and business users while maintaining strict access controls. 

FinCorp objectives 

• Centralize Data Governance: Manage data governance policies across multiple Databricks workspaces. 
• Enhance Security: Implement fine-grained access controls and data masking for sensitive information. 
• Ensure Compliance: Track data lineage and audit data access for regulatory compliance. 
• Improve Data Discovery: Provide a searchable catalog of data assets for users. 
• Facilitate Collaboration: Enable seamless data sharing and collaboration across teams. 

FinCorp’s implementation of Unity Catalog 

Step 1: Setup the metastore and attach the workspaces  

FinCorp currently operates multiple Databricks workspaces, each with its own Hive Metastore. To streamline this setup, we create a Unity Catalog metastore to centralize metadata storage. Then, we attach all of FinCorp’s relevant Databricks workspaces to the centralized metastore.  

Step 2:  Define data governance policies 

To enhance data organization and security, we create schemas and tables for different data domains, such as customer data and transaction data. We implement fine-grained access controls to restrict access to sensitive data, ensuring that only authorized users can view or modify it. Additionally, we apply data masking to sensitive columns, further protecting confidential information from unauthorized access.  

Step 3: Enable data lineage and auditing 

To ensure comprehensive data governance, we track data lineage to monitor data transformations and usage. Additionally, we use built-in auditing features to log data access and modifications.  

Step 4: Enhance data discovery  

To enhance data discovery, we tag and describe data assets to improve their discoverability. Additionally, we utilize the Databricks UI to search and explore data assets.  

Step 5: Facilitate collaboration 

To facilitate collaboration, we enable data sharing across teams using Unity Catalog’s access controls. This allows data scientists and analysts to collaborate on data projects while ensuring data security.  

Benefits 

• Centralized governance: FinCorp has established a unified platform for managing data governance policies, reducing complexity and ensuring consistency across the organization. 
• Enhanced security: The implementation of fine-grained access controls and data masking techniques ensures the protection of sensitive information. 
• Regulatory compliance: Detailed data lineage and comprehensive audit logs enable FinCorp to adhere to regulatory requirements and facilitate efficient audits. 
• Improved data discovery: Users can effortlessly locate and comprehend available data assets, boosting productivity. 
• Seamless collaboration: Teams can collaborate efficiently without compromising data security. 

Use case conclusion 

By implementing the Unity Catalog, FinCorp can effectively manage and govern its data assets, ensuring security, compliance, and efficient data usage across the organization. 

In summary  

Databrick’s Unity Catalog offers a powerful, centralized solution for data governance in the Databricks Lakehouse Platform. It simplifies the management of data assets, enhances security through fine-grained access controls, and ensures compliance with regulatory requirements.

With features like data lineage, auditing, and a searchable catalog, Unity Catalog empowers organizations to streamline their data governance processes, improve data discovery, and facilitate collaboration across teams. By adopting Unity Catalog, organizations can effectively manage their data assets, ensuring they are used efficiently and securely. 

Ready to get started? 

Are you ready to take the next steps with Databrick’s Unity Catalog? Fractal can help. Contact us to get started.