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Exam AWS Certified Machine Learning Engineer - Associate MLA-C01 All Questions

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Exam AWS Certified Machine Learning Engineer - Associate MLA-C01 topic 1 question 47 discussion

Exam question from Amazon's AWS Certified Machine Learning Engineer - Associate MLA-C01
Question #: 47
Topic #: 1
[All AWS Certified Machine Learning Engineer - Associate MLA-C01 Questions]

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?

  • A. Configure dynamic data masking policies to control how sensitive data is shared with the data scientist at query time.
  • B. Create a materialized view with masking logic on top of the database. Grant the necessary read permissions to the data scientist.
  • C. 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.
  • D. 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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Suggested Answer: A 🗳️
by GiorgioGss at Nov. 27, 2024, 10:51 p.m.
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Saransundar
1 month ago
Selected Answer: A
Amazon Redshift database → Sensitive data → Dynamic Data Masking → Query-time masking for data scientist → No transformation or additional storage → Least effort
upvoted 1 times
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GiorgioGss
1 month, 1 week ago
Selected Answer: A
https://docs.aws.amazon.com/redshift/latest/dg/t_ddm.html LEAST effort leads to A.
upvoted 1 times
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