Snowflake Data Access.pptx
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This document discusses how to set up dynamic data masking and row access policies in Snowflake. Dynamic data masking masks data at the query level based on masking policies and the user's role, without permanently altering the raw data. Row access policies use conditional expressions to determine which rows a user can see based on their role and context functions. The document outlines the processes for setting up these security features on Snowflake tables and views.
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Snowflake Data Access.pptx
- 1. 1 Analytics Snowflake - Data Access Simplified
- 2. 2 Analytics Snowflake - Dynamic Data Masking Setup Dynamic Data Masking helps to mask table’s column plan-text data masked data. This is schema level objects and currently can be applied on table & view only. Dynamic Data Masking feature is logical and applied at query time. It doesn’t mask data persistently in database. Depending on the masking policy conditions, the SQL execution context, and role hierarchy, Snowflake query operators may see the plain-text value, a partially masked value, or a fully masked value. The following figure shows the process of setting up Dynamic Data Masking in Snowflake objects.
- 3. 3 Analytics Snowflake - Dynamic Data Masking Setup
- 4. 4 Analytics Snowflake – Row Access Policy Setup A row access policy contains an expression that can specify Snowflake database objects (e.g. table or view), and use Conditional Expression Functions and Context Functions to determine which rows should be visible in a given context. Snowflake evaluates the policy expression by using the role of the policy owner, not the role of the operator who executed the query. This approach allows Snowflake not to return a row in a query result because the query operator does not require access to the mapping tables in the row access policy. The following figure shows the process of setting up Row Access Policy in Snowflake objects.
- 5. 5 Analytics Snowflake – Row Access Policy Setup