DVA-C02 · Question #638
A company stores its data in data tables in a series of Amazon S3 buckets. The company received an alert that customer credit card information might have been exposed in a data table on one of the…
The correct answer is B. Use Amazon Made to run a job on the S3 buckets that contain the affected data. Filter the. Amazon Macie is the AWS service designed to automatically discover and protect sensitive data such as credit card numbers stored in Amazon S3 buckets.
Question
A company stores its data in data tables in a series of Amazon S3 buckets. The company received an alert that customer credit card information might have been exposed in a data table on one of the company's public applications. A developer needs to identify all potential exposures within the application environment. Which solution will meet these requirements?
Options
- AUse Amazon Athena to run a job on the S3 buckets that contain the affected data. Filter the
- BUse Amazon Made to run a job on the S3 buckets that contain the affected data. Filter the
- CUse Amazon Made to run a job on the S3 buckets that contain the affected data. Filter the
- DUse Amazon Athena to run a job on the S3 buckets that contain the affected data. Filter the
How the community answered
(17 responses)- A12% (2)
- B76% (13)
- C6% (1)
- D6% (1)
Why each option
Amazon Macie is the AWS service designed to automatically discover and protect sensitive data such as credit card numbers stored in Amazon S3 buckets.
Amazon Athena is a SQL query service for analyzing structured data and requires the developer to already know what patterns to search for; it cannot automatically detect sensitive data types like credit card numbers across unknown objects.
Amazon Macie uses machine learning to automatically identify and classify sensitive data including credit card numbers, PII, and financial information in S3 buckets; it generates detailed findings that pinpoint which specific objects contain sensitive data, enabling rapid identification of all potential exposures across the environment without manual querying.
This option describes the same Macie-based approach but with incorrect or incomplete configuration compared to option B, which represents the fully correct Macie sensitive data discovery workflow.
Amazon Athena lacks built-in sensitive data detection capabilities and would require manual SQL pattern-matching queries, making it inefficient for broadly identifying unknown or undocumented exposures.
Concept tested: Amazon Macie sensitive data discovery in S3
Source: https://docs.aws.amazon.com/macie/latest/user/what-is-macie.html
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