A. Create a masking policy for the `NAME' column using a CASE statement that checks the CURRENT ROLE() and applies the mask if the role is not ACCOUNTADMIW. create a security policy for row-level filtering on the 'CITY column, checking the and to determine the appropriate filter condition. Apply the row access policy to the table.

B. Create a view on top of the 'CUSTOMER_DATA' table and implement the masking and row-level security logic within the view definition using CASE statements based on CURRENT ROLE() and CURRENT USER().

C. Create a masking policy using regular expressions to filter the data. Create a stored procedure to filter the data based on the 'CITY' column for certain users.

D. Create masking policy using the 'TRANSFORM' function to mask the 'NAME' column, and create a row access policy to filter rows based on 'CITY'. Ensure the row access policy uses a mapping table between CITY_MANAGER and CITY.

E. Create a stored procedure with 'EXECUTE AS OWNER to filter the data based on the 'CITY column for certain users, and masking policy to use `SHA256' on the 'NAME column