Amazon Web Services Data-Engineer-Associate Exam With Confidence Using Practice Dumps

Option B is correct because Amazon Q in QuickSight is the AWS feature built specifically for natural language interaction with business data. AWS documentation explains that Amazon Q in QuickSight lets users ask questions in natural language, generate summaries and data stories, and create visuals from author prompts. AWS Prescriptive Guidance also notes that users can generate insights with natural language prompts and that they do not have to write SQL queries or learn complex BI tooling. That matches the requirement that some analysts lack SQL knowledge and need to create reports frequently with minimal effort.

Option A is not the best answer because zero-ETL access addresses data movement and integration, not natural-language dashboard creation. Option C introduces another analytics platform and therefore more operational effort. Option D provides access to data, but federated querying still does not address the key requirement for natural-language dashboard and report generation for nontechnical analysts. The AWS-native feature that directly solves this problem with the least additional management is Amazon Q in QuickSight.

Option B is the best answer because Amazon EventBridge is designed to route events based on matching rules, and each rule can use a specific event pattern to match only the relevant error type and then send that event to the correct target. AWS states that EventBridge event buses receive events and deliver them to targets, and that rules can match on event details and route matching events accordingly. This makes it ideal for real-time error classification with very little custom code. An SNS topic per team then provides immediate push-based notification delivery.

Option A adds unnecessary operational overhead because Lambda would be doing routing logic that EventBridge rules already handle natively. Option C is weaker because SQS is pull-based; teams must poll queues, which is not the best fit for “without any delay” notifications. AWS documentation explicitly describes SQS consumption through polling. Option D is also not the best fit because CloudWatch alarms are threshold-based metric monitors, not event routers for per-message error classification.

This aligns with the study guide’s emphasis on using managed AWS services to automate and orchestrate pipeline actions with the least overhead.