SnowPro Advanced Data Engineer

By Snowflake · Question Mode

QuestionQ13

Implement Data Protection and Recovery

A Data Engineer has found that numerous tables in the company database include sensitive information about products that are not yet in production. The information is distributed across multiple tables and across different columns in each table. The Engineer is prioritizing protection of the data in the packaging table, with access limited to users in the researcher and marketing roles. All tables containing sensitive data must be identified to improve data-governance management.

How can these requirements be satisfied with the least operational overhead?

Explanation

Snowflake tag-based masking policies combine object tags with dynamic data masking. A masking policy can allow the researcher and marketing roles to see unmasked values while masking values for other roles. Assigning that policy to a tag and applying the tag to each sensitive table automatically protects the table’s matching columns, while the tag also identifies sensitive tables for governance. This is more scalable than assigning a policy separately to every table.

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