The correct answers are Use Amazon DynamoDB to organize employee data in hierarchical relationships. Export the data to Amazon S3 each month and Configure Amazon Macie in the account and connect it with Amazon EventBridge to deliver monthly alerts through Amazon SNS.

DynamoDB is a highly performant NoSQL database that provides sub-millisecond response times, making it ideal for applications requiring low-latency queries on high-traffic workloads. Its flexible schema design supports hierarchical data models, especially when combined with partition keys and sort keys. Exporting to S3 each month enables downstream analysis or compliance checks.

Amazon Macie is a fully managed service that uses machine learning to identify and classify sensitive data such as financial records. By integrating Macie with EventBridge and using SNS, the system can automatically notify administrators when specific patterns or data classifications are found. This meets the requirement for automated monthly compliance alerts.

The option Store the hierarchical employee data in Amazon Redshift and unload it to Amazon S3 for monthly review is incorrect because Redshift is designed for OLAP (analytical) use cases, not low-latency, high-frequency transactional queries. It doesnt provide the responsiveness needed for real-time employee lookups in a web application.

The choice Enable Amazon Athena to run queries on S3-stored employee data and visualize the results in Amazon QuickSight is also inappropriate. While this combo is useful for analysis and reporting, it does not support fast, transactional querying, and it doesnt fulfill the low-latency requirement of the application.

The response Activate Amazon Macie and route monthly detection events through EventBridge to AWS Lambda for processing adds unnecessary complexity. While valid, using Lambda for notifications introduces extra maintenance and overhead compared to directly using SNS, which is purpose-built for alerts and messages.

This question is useful because it tests your ability to combine AWS services to meet performance, security, and compliance goals. A tip for solving similar questions is to separate the problem into partsdata structure and latency vs. security and notificationand then match the services to each part. Macie is the go-to tool for sensitive data detection, while DynamoDB is best suited for fast, hierarchical lookups.

The tricky part of this question is avoiding seemingly valid analytical tools like Redshift or Athena, which do not align with the real-time performance requirement. Its essential to distinguish transactional from analytical workloads in scenarios like this.

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