AWS Certified Machine Learning Engineer – Associate (MLA-C01) — Question 111

A medical company needs to store clinical data. The data includes personally identifiable information (PII) and protected health information (PHI).

An ML engineer needs to implement a solution to ensure that the PII and PHI are not used to train ML models.

Which solution will meet these requirements?

Answer options

• A. Store the clinical data in Amazon S3 buckets. Use AWS Glue DataBrew to mask the PII and PHI before the data is used for model training.
• B. Upload the clinical data to an Amazon Redshift database. Use built-in SQL stored procedures to automatically classify and mask the PII and PHI before the data is used for model training.
• C. Use Amazon Comprehend to detect and mask the PII before the data is used for model training. Use Amazon Comprehend Medical to detect and mask the PHI before the data is used for model training.
• D. Create an AWS Lambda function to encrypt the PII and PHI. Program the Lambda function to save the encrypted data to an Amazon S3 bucket for model training.

Correct answer: C

Explanation

Option C is correct because Amazon Comprehend and Amazon Comprehend Medical are specifically designed to identify and mask PII and PHI, ensuring compliance with data protection requirements. Options A and B do not provide specific tools for identifying and masking sensitive information effectively, while option D focuses on encryption, which does not prevent the data from being used in its original form during training.