試験ADA-C01 トピック2 問題45 スレッド
Snowflake ADA-C01のリアル試験問題集
問題 #: 45
トピック #: 2
問題 #: 45
トピック #: 2
What are characteristics of Dynamic Data Masking? (Select TWO).
おすすめの解答:B,E 解答を投票する
Explanation
According to the Using Dynamic Data Masking documentation, Dynamic Data Masking is a feature that allows you to alter sections of data in table and view columns at query time using a predefined masking strategy. The following are some of the characteristics of Dynamic Data Masking:
*A single masking policy can be applied to columns in different tables. This means that you can write a policy once and have it apply to thousands of columns across databases and schemas.
*A single masking policy can be applied to columns with different data types. This means that you can use the same masking strategy for columns that store different kinds of data, such as strings, numbers, dates, etc.
*A masking policy that is currently set on a table can be dropped. This means that you can remove the masking policy from the table and restore the original data visibility.
*A masking policy can be applied to the VALUE column of an external table. This means that you can mask data that is stored in an external stage and queried through an external table.
*The role that creates the masking policy will always see unmasked data in query results. This is not true, as the masking policy can also apply to the creator role depending on the execution context conditions defined in the policy. For example, if the policy specifies that only users with a certain custom entitlement can see the unmasked data, then the creator role will also need to have that entitlement to see the unmasked data.
According to the Using Dynamic Data Masking documentation, Dynamic Data Masking is a feature that allows you to alter sections of data in table and view columns at query time using a predefined masking strategy. The following are some of the characteristics of Dynamic Data Masking:
*A single masking policy can be applied to columns in different tables. This means that you can write a policy once and have it apply to thousands of columns across databases and schemas.
*A single masking policy can be applied to columns with different data types. This means that you can use the same masking strategy for columns that store different kinds of data, such as strings, numbers, dates, etc.
*A masking policy that is currently set on a table can be dropped. This means that you can remove the masking policy from the table and restore the original data visibility.
*A masking policy can be applied to the VALUE column of an external table. This means that you can mask data that is stored in an external stage and queried through an external table.
*The role that creates the masking policy will always see unmasked data in query results. This is not true, as the masking policy can also apply to the creator role depending on the execution context conditions defined in the policy. For example, if the policy specifies that only users with a certain custom entitlement can see the unmasked data, then the creator role will also need to have that entitlement to see the unmasked data.
Nakayama 2026-01-07 11:04:15
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