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Data Quality
Assure reliability, consistency, and accuracy data from different sources to deliver value to employees and customers.
Data Quality Catalogs
The Data Integrity Suite Data Catalog lets users discover and understand connected data sources.
Reference
Data Catalog views
Databricks
Data Catalog displays dataset structure for a cataloged Databricks connection.

Welcome
The Precisely Data Integrity Suite is designed to deliver trusted data with accuracy, consistency, and context – built on the core capabilities of data integration, data quality, data governance, location intelligence, and data enrichment.
Data Integration
Replicate data from mainframe, IBM i, and relational databases to cloud analytics platforms.
Data Observability
Proactively monitor and manage the health of your data. Receive actionable insights through alerts that drive business decisions.
Data Governance
Manage data policy and processes with greater insight into your data's meaning, lineage, and impact.
Data Quality
Assure reliability, consistency, and accuracy data from different sources to deliver value to employees and customers.
- Data Quality Catalogs
  The Data Integrity Suite Data Catalog lets users discover and understand connected data sources.
  - About Data Catalog
    The Precisely Data Catalog is a cloud service that lets users discover and understand connected data sources.
  - Using Data Catalog
  - How to
  - Reference
    - Data Catalog views
      - Databricks
        Data Catalog displays dataset structure for a cataloged Databricks connection.
- Data Quality datasets
  A dataset defines a data source and characterizes data to be loaded and transformed by pipelines.
- Data Quality pipelines
  Pipelines define and apply transforms to data loaded by a dataset.
- Data Quality jobs
- Data Connections
  Connecting to data is the first step in processing, analyzing, and storing information.
Administration
Manage your subscription, your users and their roles, and other system tasks.

Databricks dataset (Data Catalog)

Data Catalog displays dataset structure for a cataloged Databricks connection.

This view is displayed by clicking Data Catalog Image of the Data Catalog icon and browsing tables in a Databricks. The top left corner shows the name and type (such as Table) of the cataloged dataset.

Details

Connection: The cataloged data connection.
Schema: The schema for the currently selected dataset. A schema encapsulates metadata for a dataset in a connected data source.
Last updated on: Shows the date and time that the connection was updated. The table view does not show any changes in the data source after the last update.; Shows the date and time that the data asset was updated. Any changes in the data source made after that time will not appear in Data Integrity Suite.

Dataset fields

Field Name: Shows the name for each field in the dataset.
Data Type: Shows the data type for each field in the dataset.
Semantic Type: Shows the semantic type defined for a field. This is empty when no semantic type exists for a field.