by Paul Roome and Sachin Thakur
Databricks Unity Catalog simplifies data and AI governance by providing a unified solution for organizations to securely discover, access, monitor, and collaborate on a range of data and AI assets. This includes tables, ML models, files and functions, ultimately boosting productivity and unlocking the full potential of the Lakehouse environment.
Today, we're excited to announce that Unity Catalog is now pre-configured and accessible in new premium workspaces on AWS and Azure, marking a significant milestone in our journey. Rollout for this feature will proceed gradually across accounts and regions. Reach out to your account representative for more details.
You’ll notice a few new features in your workspace.
Now that your workspace has access to Unity Catalog, a whole host of features become available to you! Here are three things that you should try today using the notebook!
Democratizing data and AI requires ensuring the accessibility and security of data and AI assets. Unity Catalog simplifies this process by providing users with a central hub for effortlessly managing their data and AI resources. This empowers users to generate tables, AI models, functions, and files and catalog them in one place while maintaining access controls and auditability.
Watch the demo below to see how you can register data and AI assets and define access permissions.
Unity Catalog offers real-time inference of data lineage for all your workloads, down to the column level. This feature helps you build trust in your data and AI assets, conduct impact analysis, and fuel data discovery for your end users
Watch the demo below to see data lineage in action.
Unity Catalog streamlines access policy administration, enabling the creation of fine-grained permissions at both row and column levels for your Databricks workloads. Its cloud-agnostic SQL-based interface ensures a straightforward and user-friendly experience. Explore the guides (AWS, Azure, and GCP) to learn more about row filters and column masks in Unity Catalog.
Watch the demo below to see column-masking in Unity Catalog.
By adopting Unity Catalog as the cornerstone of your Lakehouse architecture, you unlock the potential of a flexible and scalable governance solution that spans your entire data and AI ecosystem. For comprehensive documentation, refer to the Unity Catalog guides available for AWS, Azure, and GCP. For additional tutorials, please visit Databricks Demo Center for more tutorials on Unity Catalog. Download the free eBook on Data and AI governance to learn more about how Databricks Lakehouse Platform addresses data and AI governance challenges.