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Data Sources in Immuta

Data owners expose their data across their organization to other users by registering that data in Immuta as a data source. When data is registered, Immuta does not affect existing policies on those tables in the remote system (unless an existing global policy in Immuta applies to the data source), so users who had access to a table before it was registered can still access that data without interruption.

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Data sources with nested columns

When data sources support nested columns, these columns get parsed into a nested Data Dictionary. Below is a list of data sources that support nested columns:

  • S3

  • Azure Blob

  • Databricks sources with complex data types enabled

    • When complex types are enabled, Databricks data sources can have columns that are arrays, maps, or structs that can be nested.

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Data source user roles

There are various roles users and groups can play relating to each data source. These roles are managed through the members tab of the data source. Roles include the following types:

  • Owners: Those who create and manage new data sources and their users, documentation, and data dictionaries.

  • Subscribers: Those who have access to the data source data. With the appropriate data accesses and attributes, these users and groups can view files, run queries, and generate analytics against the data source data. All users and groups granted access to a data source have subscriber status.

  • Experts: Those who are knowledgeable about the data source data and can elaborate on it. They are responsible for managing the data source's documentation and data dictionary tags and descriptions.

See Manage data source members for a tutorial on modifying user roles.

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Data dictionary

The data dictionary provides information about the columns within the data source, including column names and value types.

Dictionary columns are automatically generated when the data source is created. However, data owners and experts can tag columns in the data dictionary and add descriptions to these entries.

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Data dictionary column icons

The data dictionary displays icons on columns that have a masking policy applied to them. The appearance of these icons varies depending on the permission of the user.

Governors and data owners

If you have the GOVERNANCE permission or are the data source owner, the data dictionary column icons will appear in these ways:

  • No icon: No masking policy applies to the column.

  • Yellow eye: A masking policy applies to the column, but the column is unmasked for the current user because they meet the exception criteria for the policy.

  • Red eye: A policy on the column masks it for the current user.

All other users

The data dictionary column icons will appear in these ways for all other users:

  • No icon: Either no masking policy applies to the column or a masking policy applies to the column, but the column is unmasked for the current user because they meet the exception criteria for the policy.

  • Red eye: A policy on the column masks it for the current user.

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Audit

The following events related to data sources are audited and can be found on the audit page in the UI:

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