Q98 — AWS SAA-C03 Ch.10

Question 98 of 100 | ← Chapter 10

Q698. A marketing team wants to build a campaign for an upcoming multi-sport event. The team has news reports from the past five years in PDF format. The team needs a solution to extract insights about the content and the sentiment of the news reports. The solution must use Amazon Textract to process the news reports.Which solution will meet these requirements with the LEAST operational overhead?

Correct Answer: C. Provide the extracted insights to Amazon Comprehend for analysis. Save the analysis to an Amazon S3 bucket

Explanation

To meet the requirements of extracting insights about the content and sentiment of news reports using Amazon Textract with the least operational overhead, the following solution should be implemented:C. Provide the extracted insights to Amazon Comprehend for analysis. Save the analysis to an Amazon S3 bucket.Option C provides a streamlined solution with minimal operational overhead for extracting insights and analyzing the content and sentiment of news reports:- Provide the extracted insights to Amazon Comprehend for analysis: Amazon Comprehend is a natural language processing (NLP) service that can analyze text and extract insights such as sentiment, entities, key phrases, and more. By providing the extracted insights from Amazon Textract to Amazon Comprehend, you can leverage its NLP capabilities to analyze the news reports.- Save the analysis to an Amazon S3 bucket: Amazon Comprehend can output the analysis results in a structured format, such as JSON. By saving the analysis to an Amazon S3 bucket, you can store the results for further processing or analysis.Option A, providing the extracted insights to Amazon Athena for analysis and storing the insights and analysis in an Amazon S3 bucket, requires additional setup and configuration for querying the data using SQL-like queries in Athena. While it provides flexibility for analysis, it introduces more operational overhead.Option B, storing the extracted insights in an Amazon DynamoDB table and using Amazon SageMaker to build a sentiment model, involves additional setup and management of DynamoDB tables and the training and deployment of a machine learning model with SageMaker. This option introduces significant operational overhead compared to the other options.Option D, storing the extracted insights in an Amazon S3 bucket and using Amazon QuickSight to visualize and analyze the data, focuses on visualization rather than the content and sentiment analysis of the news reports. QuickSight is a business intelligence tool and may not provide the necessary NLP capabilities for extracting insights.Therefore, the best solution is C: Provide the extracted insights to Amazon Comprehend for analysis and save the analysis to an Amazon S3 bucket. This solution leverages the NLP capabilities of Amazon Comprehend while minimizing operational overhead.