Demo | Protecting Sensitive Data With Projection And Aggregation Policies In Snowflake

When it comes to sensitive, proprietary, or regulated data, companies often restrict all access to ensure the data is protected. Snowflake’s privacy-enhancing technologies allow companies to unlock value from sensitive data through collaboration. Data can be accessed in more breadth by more people and analyzed more granularly, while constraints are applied to ensure sensitive data is protected and cannot be identified. Watch this demo to see how you can apply advanced privacy policies in Snowflake.
Projection Policies block queries that enumerate values of designated columns while allowing them in operations like Filter, Group, and Join. Aggregation Policies only allow aggregate queries that have more than a specified minimum number of rows.
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[@farhadkhalili1]

Whats the difference between Projection and Data Masking? Both kind of serve a similar function?

[@Amarjeet-fb3lk]

Data masking allows column to be selected,you can select the column,but you will see masked data,like 124xxxx.
But
In projection policy,you cannot select the columns on which this policy is applied.
You can use it in group by or join.