Databricks Unity Catalog assets

The Databricks Unity Catalog integration for metadata uses a specific subset of asset types. These are available out of the box. For more information on asset attributes or metadata synchronized per asset type, go to Integrated Databricks Unity Catalog data.

Tip In the latest UI, you can also integrate Databricks AI models.

Asset type	Description
Technology Asset System	Executable software that you can buy commercially off the shelf (COTS) or build internally to automate one or more business functions that help run a business smoothly and efficiently. Examples: CRM, ERP, EDW
Technology Asset Database	A collection of data that is systematically organized or structured to make it easy to create, update, and query the information. Examples: Ora_DGC_V45, SalesDB2020
Data Asset Data Structure Schema	An asset that contains the location of specific data. It provides all the details that are required for setting up a connection to a database or server.
Data Asset Data Structure Table	An implementation of data entities in columns and rows, in a given database system. It is the basic structure of a relational database. Examples: Account_tbl, CUST_ADDR
Data Asset Data Structure Database View	A Database View is a virtual table based on the result-set of an SQL statement. Database View assets in Collibra represent Views and Metric Views in Databricks Unity Catalog.
Data Asset Data Element Column	An atomic unit of data that can be stored in a database table. Examples: FST_NM, EMPID

Databricks Unity Catalog diagram view for metadata synchronization

Asset type	Description
Databricks AI Model Version	A subtype of AI Model Version that represents AI model versions in Databricks AI.
AI Model Deployment	The operational instance where a model version is assigned computational resources to execute and generate real-time outputs.
AI Base Model	Represents foundational models used in your Databricks AI workspace.
AI Endpoint	The access point for external systems that provides a consistent interface while allowing for the seamless exchange of underlying deployments.
AI Monitor	The configuration of automated tracking parameters and alerting thresholds used to observe a deployment’s real-world performance and detect deviations from expected behavior.