A. Create separate views for analysts and data scientists, applying masking policies within the views, and grant access to these views based on their respective roles. Additionally, grant the compliance role direct access to the base table.

B. Create masking policies on the 'SSN' , and 'ADDRESS' columns. Use conditional masking expressions based on the CURRENT ROLE() function to determine what data to show to each role (analysts, data scientists, compliance).

C. Use data encryption for the entire 'CUSTOMER_DATA table and provide decryption keys to specific roles based on their access requirements. Provide the compliance role with the master key.

D. Create dynamic data masking policies on each sensitive column in the 'CUSTOMER_DATA table, associating these policies with specific roles using Snowflake's tag-based masking. Grant roles only the privileges needed to select the columns based on their requirements.

E. Replicate the CUSTOMER_DATA table three times, once for each user group (Analysts, Data Scientist and Compliance). Mask sensitive information by altering the data with the respective masking function.