Key vault configuration - Precisely Data Integrity Suite

Data Integrity Suite

Product
Spatial_Analytics
Data_Integration
Data_Enrichment
Data_Governance
Precisely_Data_Integrity_Suite
geo_addressing_1
Data_Observability
Data_Quality
dis_core_foundation
Services
Spatial Analytics
Data Integration
Data Enrichment
Data Governance
Geo Addressing
Data Observability
Data Quality
Core Foundation
ft:title
Data Integrity Suite
ft:locale
en-US
PublicationType
pt_product_guide
copyrightfirst
2000
copyrightlast
2026

This section provides you the key vault configuration used for Databricks datasource type in Data Integrity Suite.

Field Description
Authentication method Select the authentication method to use for connecting to Databricks. Two options are available:
  • Regular: Uses standard token authentication.
  • Key Vault: Uses credentials stored securely in a key vault for enhanced security.
When key vault authentication method is used, configure the following fields
Key vault setup Specifies the method used to authenticate with Databricks which can be retrieved from a key vault:
  1. Key vault: Specifies the preconfigured key vault to be used for retrieving the secret credentials.
  2. Authentication token secret path: Specifies the path or identifier within the selected key vault where the secret access key is stored. Example: secret/aws/s3/accesskey.

Add key vault: Specifies the option to configure and register a new key vault if one is not already available in the list. For configuration steps, refer to key vault setup.

Processing Environment for Cataloging Specifies the environment used for managing and organizing data catalogs. It provides two options:
  • Databricks Cluster: Select this option if you are using a Databricks cluster for data processing and cataloging. If this option is selected, also specify the relevant Databricks cluster. Example: Cluster-1
    • Catalog: Specifies name of the catalog where data is stored and managed. The default value is hive_metastore.
  • Databricks SQL Warehouse: Choose this option if you are utilizing a Databricks SQL Warehouse for data management and querying, also specify the relevant Databricks SQL warehouse. Example: SQLWarehouse-1.
    • Catalog: Specifies name of the catalog where data is stored and managed. The default value is hive_metastore.
  • Databricks Notebooks: Executes cataloging operations using Databricks Notebooks, which are collaborative, interactive environments within Databricks
    • Username: The email ID of the Databricks user or service principal. This is a mandatory field.
    • Directory Filter: Restricts cataloging to specific directories or workspace paths within the Databricks workspace. Specify one or more workspace path patterns using forward slashes (/) to limit the cataloging scope to relevant notebook assets. This is a mandatory field. The filter supports:
      • Exact folder paths
      • Wildcard matching
      • Recursive folder matching
      • Multiple comma-separated path patterns

      By default, Databricks user notebooks are typically stored under: /Users/<email-id>/

      Examples:

      • /Users/<email-id>/** : Catalogs all folders and notebooks under the specified user workspace path. ** indicates recursive matching for all folders and notebooks.

      • /Users/<email-id>/Folder1: Catalogs all notebooks within the specific folder Folder1.
      • /Users/<email-id>/Folder1,/Users/<email-id>/Folder2 : Catalogs notebooks from multiple specified folders.