AWS Certified Data Engineer - Associate DEA-C01Demo

By Amazon · Question Mode

QuestionQ80

Data Ingestion and Transformation

A global ecommerce company occasionally receives customer data files in its Amazon S3 data lake. The company needs to automatically detect new data and mask sensitive data before making the data available to the company's analytics team.

Which solution will meet these requirements with the LEAST operational overhead?

  • A Configure Amazon S3 Event Notifications to detect the new data and trigger an AWS Glue job. Use Amazon Macie to detect and mask the sensitive data. Store the processed data in Amazon Redshift.
  • B Use Amazon Managed Streaming for Apache Kafka (Amazon MSK) to detect incoming data. Use Amazon EMR workflows to detect and mask sensitive data. Store the processed data in Amazon S3.
  • C Use Amazon Kinesis Data Streams to capture new data. Use Amazon Comprehend to detect and mask the sensitive data. Store the processed data in Amazon DynamoDB tables.
  • D Use Amazon EventBridge to detect new data and run AWS Glue workflows. Use AWS Glue DataBrew to detect and mask the sensitive data. Store the processed data in an S3 bucket.
Explanation

Amazon EventBridge can automatically detect new object arrivals and trigger AWS Glue workflows with no custom polling code, and AWS Glue DataBrew includes built-in transformations to detect and redact or mask sensitive data (such as PII) as part of that same workflow, writing masked output back to S3. Amazon Macie only classifies and reports on sensitive data; it cannot transform or mask it, so it cannot fulfill the masking requirement on its own. Learn more: AWS Glue DataBrew PII data handling

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