Key takeaways
- Snowflake has launched Data Classification in public preview, integrated into its platform at no extra cost.
- The feature aims to streamline data governance by eliminating manual processes and reliance on third-party tools.
- Data Classification helps organisations analyse and categorise sensitive data, enhancing protection and access management.
- It uses machine learning to identify personal information that requires additional security measures.
- Currently, the focus is on direct identifiers, quasi-identifiers, and sensitive attributes, with plans for more categories.
Snowflake has made Data Classification available in public preview. The Data Classification is built into Snowflake’s platform and is available to the users' at no extra cost.
Snowflake’s Data Classification aims at helping organisations govern sensitive data by removing manual processes or dependence on a third-party tool. Organisations can leverage Data Classification to understand their data and unlock the analytical value present in the data. Once classified using Snowflake’s Data Classification, organisations can easily run queries defined in INFORMATION_SCHEMA to search for this data, protect it with role-based policies, and audit access through Access History, which is all part of Snowflake’s suite of native data governance features.
Data Classification analyses the contents and metadata of columns in a table and then feeds that information into a pre-built machine learning model to help determine the appropriate categories of personal information that may be considered sensitive, requiring more protection or limited access, and applies the results as System Tags. Snowflake will continue to add more categories giving customers more functionality with little additional input.
Currently, Snowflake’s Data Classification focuses on direct identifiers, quasi-identifiers, and sensitive attributes.
