Data Governance in Snowflake¶
Snowflake provides industry-leading features that ensure the highest levels of governance for your account and users, as well as all the data you store and access in Snowflake.
- Data Quality Monitoring and data metric functions
Allows the monitoring of the state and integrity of your data using system data metric functions and user-defined data metric functions.
- Column-level Security
Allows the application of a masking policy to a column within a table or view.
- Row-level Security
Allows the application of a row access policy to a table or view to determine which rows are visible in the query result.
- Introduction to object tagging
Allows the tracking of sensitive data for compliance, discovery, protection, and resource usage.
- Tag-based masking policies
Allows protecting column data by assigning a masking policy to a tag and then setting the tag on a database object or the Snowflake account.
- Sensitive data classification
Allows categorizing potentially personal and/or sensitive data to support compliance and privacy regulations.
- Access History
Allows the auditing of the user access history through the Account Usage ACCESS_HISTORY view.
- Object Dependencies
Allows the auditing of how one object references another object by its metadata (e.g. creating a view depends on a table name and column names) through the Account Usage OBJECT_DEPENDENCIES view.
- Data Governance area in Snowsight
Allows you to use the Governance & security » Tags & policies area to monitor tags and policies across taggable object types, work with tagged objects, and (in public preview) create tags in Snowsight. The Dashboard, Tagged objects, and Tags tabs support these workflows. For details, see: