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Question 882 - SAA-C03 discussion

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A company tracks customer satisfaction by using surveys that the company hosts on its website. The surveys sometimes reach thousands of customers every hour. Survey results are currently sent in email messages to the company so company employees can manually review results and assess customer sentiment.

The company wants to automate the customer survey process. Survey results must be available for the previous 12 months.

Which solution will meet these requirements in the MOST scalable way?

A.

Send the survey results data to an Amazon API Gateway endpoint that is connected to an Amazon Simple Queue Service (Amazon SQS) queue. Create an AWS Lambda function to poll the SQS queue, call Amazon Comprehend for sentiment analysis, and save the results to an Amazon DynamoDB table. Set the TTL for all records to 365 days in the future.

Answers
A.

Send the survey results data to an Amazon API Gateway endpoint that is connected to an Amazon Simple Queue Service (Amazon SQS) queue. Create an AWS Lambda function to poll the SQS queue, call Amazon Comprehend for sentiment analysis, and save the results to an Amazon DynamoDB table. Set the TTL for all records to 365 days in the future.

B.

Send the survey results data to an API that is running on an Amazon EC2 instance. Configure the API to store the survey results as a new record in an Amazon DynamoDB table, call Amazon Comprehend for sentiment analysis, and save the results in a second DynamoDB table. Set the TTL for all records to 365 days in the future.

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B.

Send the survey results data to an API that is running on an Amazon EC2 instance. Configure the API to store the survey results as a new record in an Amazon DynamoDB table, call Amazon Comprehend for sentiment analysis, and save the results in a second DynamoDB table. Set the TTL for all records to 365 days in the future.

C.

Write the survey results data to an Amazon S3 bucket. Use S3 Event Notifications to invoke an AWS Lambda function to read the data and call Amazon Rekognition for sentiment analysis. Store the sentiment analysis results in a second S3 bucket. Use S3 Lifecycle policies on each bucket to expire objects after 365 days.

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C.

Write the survey results data to an Amazon S3 bucket. Use S3 Event Notifications to invoke an AWS Lambda function to read the data and call Amazon Rekognition for sentiment analysis. Store the sentiment analysis results in a second S3 bucket. Use S3 Lifecycle policies on each bucket to expire objects after 365 days.

D.

Send the survey results data to an Amazon API Gateway endpoint that is connected to an Amazon Simple Queue Service (Amazon SQS) queue. Configure the SQS queue to invoke an AWS Lambda function that calls Amazon Lex for sentiment analysis and saves the results to an Amazon DynamoDB table. Set the TTL for all records to 365 days in the future.

Answers
D.

Send the survey results data to an Amazon API Gateway endpoint that is connected to an Amazon Simple Queue Service (Amazon SQS) queue. Configure the SQS queue to invoke an AWS Lambda function that calls Amazon Lex for sentiment analysis and saves the results to an Amazon DynamoDB table. Set the TTL for all records to 365 days in the future.

Suggested answer: A

Explanation:

This solution is the most scalable and efficient way to handle large volumes of survey data while automating sentiment analysis:

API Gateway and SQS: The survey results are sent to API Gateway, which forwards the data to an SQS queue. SQS can handle large volumes of messages and ensures that messages are not lost.

AWS Lambda: Lambda is triggered by polling the SQS queue, where it processes the survey data.

Amazon Comprehend: Comprehend is used for sentiment analysis, providing insights into customer satisfaction.

DynamoDB with TTL: Results are stored in DynamoDB with a Time to Live (TTL) attribute set to expire after 365 days, automatically removing old data and reducing storage costs.

Option B (EC2 API): Running an API on EC2 requires more maintenance and scalability management compared to API Gateway.

Option C (S3 and Rekognition): Amazon Rekognition is for image and video analysis, not sentiment analysis.

Option D (Amazon Lex): Amazon Lex is used for building conversational interfaces, not sentiment analysis.

AWS

Reference:

Amazon Comprehend for Sentiment Analysis

Amazon SQS

DynamoDB TTL

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asked 27/10/2024
Dustin Roberts
45 questions
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