Data Access Management > Data access policies > Data access control policy permission mappings
  

Data access control policy permission mappings

When you configure a data access control policy to grant data access permissions to a user in a source system, bear in mind that different platforms apply the policy permissions in different ways.
The following table lists the permissions that you can configure in a data access control policy and the corresponding permissions that the policy enables in source systems:
Source System
read
write
delete
Amazon Redshift
select
insert
update
delete
Amazon S3
s3:GetObject
s3:ListBucket
s3:PutObject
s3:RestoreObject
s3:AbortMultipartUpload
s3:ListMultipartUploadParts
s3:DeleteObject
Databricks
select
modify
(not applicable)
Google BigQuery
bigquery.tables.getData
bigquery.tables.updateData (grants insert, update and delete)
bigquery.tables.updateData (grants insert, update and delete)
Microsoft Fabric Data Lakehouse
select
insert
update
delete
Microsoft Fabric Data Warehouse
select
insert
update
delete
Microsoft Power BI
For Power BI workspaces: Viewer role
For Power BI data sets: Viewer role
For Power BI workspaces: Contributor role
Not applicable for Power BI data sets
(not applicable)
Snowflake
select
insert
update
delete
Tableau
view template
For Tableau projects: publish template
For Tableau workbooks: download, edit, overwrite, save as
For Tableau data sources: download, overwrite, save as
For Tableau data sheets: download, edit
delete (not applicable for Tableau projects)

Guidelines

Note the following guidelines when you configure data access control policy permissions:

General

Databricks

Google BigQuery

Microsoft Power BI

Microsoft Fabric Data Warehouse

Users must have read access in addition to delete access in order to delete a table or view.

Snowflake

For Snowflake catalogs, Data Access Management grants user permissions to databases and schemas.