AWS Certified Machine Learning – Specialty — Question 290
A company processes millions of orders every day. The company uses Amazon DynamoDB tables to store order information. When customers submit new orders, the new orders are immediately added to the DynamoDB tables. New orders arrive in the DynamoDB tables continuously.
A data scientist must build a peak-time prediction solution. The data scientist must also create an Amazon QuickSight dashboard to display near real-time order insights. The data scientist needs to build a solution that will give QuickSight access to the data as soon as new order information arrives.
Which solution will meet these requirements with the LEAST delay between when a new order is processed and when QuickSight can access the new order information?
Answer options
- A. Use AWS Glue to export the data from Amazon DynamoDB to Amazon S3. Configure QuickSight to access the data in Amazon S3.
- B. Use Amazon Kinesis Data Streams to export the data from Amazon DynamoDB to Amazon S3. Configure QuickSight to access the data in Amazon S3.
- C. Use an API call from QuickSight to access the data that is in Amazon DynamoDB directly.
- D. Use Amazon Kinesis Data Firehose to export the data from Amazon DynamoDB to Amazon S3. Configure QuickSight to access the data in Amazon S3.
Correct answer: D
Explanation
Amazon Kinesis Data Firehose is the most efficient service for streaming real-time data from Amazon DynamoDB into Amazon S3 with minimal latency, making it quickly available for Amazon QuickSight analysis. AWS Glue is a batch-oriented service that introduces significant delay, while Kinesis Data Streams cannot write directly to S3 without a consumer like Firehose. QuickSight does not natively support direct queries on DynamoDB tables, and doing so would negatively impact the production database's performance.