Topic 1 Question 47
A company is using an Amazon Redshift database as its single data source. Some of the data is sensitive. A data scientist needs to use some of the sensitive data from the database. An ML engineer must give the data scientist access to the data without transforming the source data and without storing anonymized data in the database. Which solution will meet these requirements with the LEAST implementation effort?
Configure dynamic data masking policies to control how sensitive data is shared with the data scientist at query time.
Create a materialized view with masking logic on top of the database. Grant the necessary read permissions to the data scientist.
Unload the Amazon Redshift data to Amazon S3. Use Amazon Athena to create schema-on-read with masking logic. Share the view with the data scientist.
Unload the Amazon Redshift data to Amazon S3. Create an AWS Glue job to anonymize the data. Share the dataset with the data scientist.
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コメント(2)
- 正解だと思う選択肢: A
https://docs.aws.amazon.com/redshift/latest/dg/t_ddm.html LEAST effort leads to A.
👍 1GiorgioGss2024/11/27 - 正解だと思う選択肢: A
Amazon Redshift database → Sensitive data → Dynamic Data Masking → Query-time masking for data scientist → No transformation or additional storage → Least effort
👍 1Saransundar2024/12/05
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