Dynamic Data Masking (DDM) can mask sensitive data in the SQL Editor query result based on the context. It helps organizations to protect sensitive data from being exposed to unauthorized users.

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Configure Dynamic Data Masking

• Workspace-level admins configure the Global Masking Rule, Semantic Types, and Masking Algorithm.
• Project-level owners configure the Column Masking on the table column. This is only needed when the global masking rule is not applicable to a particular project.
• Workspace-level admins or project-level owners grant Masking Exemption to the users to access the unmasked data.
• For document databases (MongoDB and Elasticsearch), masking is configured per-collection through the Catalog — see Document Database Masking. Global masking rules and masking exemption are not supported for document databases.

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Determine whether to mask data

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Masking precedence

1. Masking Exemption. If user has been granted exemption, the data will not be masked.
2. Global Masking Rule. If no exemption is granted, the global masking rule will be applied.
3. Column Masking. If no global masking rule is configured, the column masking will be applied.

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Masking algorithm

The global masking rule and column masking are both mapped to the Semantic Types. The semantic type determines the masking algorithm.

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Masking propagation

When a column in a database table is masked, the masking effect is infectious in the sense that it propagates to any views or derived structures that depend on that column. This ensures that the protection applied to the underlying data is consistently enforced, even when accessed through alternative pathways like views.