AWS Certified Data Analytics – Specialty — Question 22

A company developed a new elections reporting website that uses Amazon Kinesis Data Firehose to deliver full logs from AWS WAF to an Amazon S3 bucket.
The company is now seeking a low-cost option to perform this infrequent data analysis with visualizations of logs in a way that requires minimal development effort.
Which solution meets these requirements?

Answer options

• A. Use an AWS Glue crawler to create and update a table in the Glue data catalog from the logs. Use Athena to perform ad-hoc analyses and use Amazon QuickSight to develop data visualizations.
• B. Create a second Kinesis Data Firehose delivery stream to deliver the log files to Amazon OpenSearch Service (Amazon Elasticsearch Service). Use Amazon ES to perform text-based searches of the logs for ad-hoc analyses and use OpenSearch Dashboards (Kibana) for data visualizations.
• C. Create an AWS Lambda function to convert the logs into .csv format. Then add the function to the Kinesis Data Firehose transformation configuration. Use Amazon Redshift to perform ad-hoc analyses of the logs using SQL queries and use Amazon QuickSight to develop data visualizations.
• D. Create an Amazon EMR cluster and use Amazon S3 as the data source. Create an Apache Spark job to perform ad-hoc analyses and use Amazon QuickSight to develop data visualizations.

Correct answer: A

Explanation

Option A is the best choice as it effectively combines AWS Glue for cataloging, Athena for queries, and QuickSight for visualization, all with minimal development effort and cost. Other options, while functional, either involve more complex setups (like creating additional services or clusters) or higher costs, making them less suitable for infrequent analysis.