Required permissions in Databricks for performing essential operations

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

To effectively perform the operations in Databricks, users must be granted the required permissions. The following document outlines the permissions required, their scope, and the associated Databricks objects.

Basic user entitlements

These are inherited via the users group.
  • Workspace Access: Permission to access the Databricks workspace.
  • Databricks SQL Access: Permission to use Databricks SQL features.

Additional entitlements required

  • Unrestricted Cluster Creation: Users must have the Allow unrestricted cluster creation entitlement to create and manage clusters necessary for running data quality tasks.

Permissions

  • All-Purpose Cluster: Users need the Can Restart permission on targeted clusters.
  • SQL Warehouse: Can use permission is required on targeted SQL warehouse.
  • Instance Pool: Can Attach To permission is needed for users to assign job clusters to instance pools, optimizing compute resources.

Required permissions in Databricks to access hive_metastore or unity catalog

Appropriate privileges must be granted on catalogs, schemas, or tables to enable data access. These privileges can be granted based on how users choose to manage the data.

Catalog

  • USE CATALOG

Schema

  • USE SCHEMA

  • SELECT

  • CREATE

  • MODIFY

Note: Modify schema and create table permissions are necessary to create or modify target table in the data quality pipeline.

Table

  • SELECT

Tip: You must have SELECT permissions on source tables to read the data. For the target table, you will require sufficient privileges to perform operations that include select, create and modify.
Note: These permissions can be set from the Databricks portal. Please refer to the steps below.
The steps outlined below are at the schema level. Similar operations can be performed, and permissions can be set at the catalog and table level.
  1. Login to the Databricks portal.
  2. Click Catalog.
  3. Select the specific schema.
  4. Navigate to the permissions tab.
  5. Click Grant.
  6. Assign the required permissions.
  7. Click Confirm.

    This will grant the required permissions to the selected users.

Advanced permissions for tables with row filter and column mask policies

  • If data quality operations are to be performed on tables using row filter and column mask policies, the workspace must have the Serverless Compute feature enabled, and users must have appropriate policy permissions in place.