AWS Certified Data Engineer – Associate (DEA-C01) — Question 217

A company wants to combine data from multiple software as a service (SaaS) applications for analysis.

A data engineering team needs to use Amazon QuickSight to perform the analysis and build dashboards. A data engineer needs to extract the data from the SaaS applications and make the data available for QuickSight queries.

Which solution will meet these requirements in the MOST operationally efficient way?

Answer options

• A. Create AWS Lambda functions that call the required APIs to extract the data from the applications. Store the data in an Amazon S3 bucket. Use AWS Glue to catalog the data in the S3 bucket. Create a data source and a dataset in QuickSight.
• B. Use AWS Lambda functions as Amazon Athena data source connectors to run federated queries against the SaaS applications. Create an Athena data source and a dataset in QuickSight.
• C. Use Amazon AppFlow to create a flow for each SaaS application. Set an Amazon S3 bucket as the destination. Schedule the flows to extract the data to the bucket. Use AWS Glue to catalog the data in the S3 bucket. Create a data source and a dataset in QuickSight.
• D. Export data the from the SaaS applications as Microsoft Excel files. Create a data source and a dataset in QuickSight by uploading the Excel files.

Correct answer: C

Explanation

Option C is the most operationally efficient solution as Amazon AppFlow is specifically designed to connect and transfer data from SaaS applications directly to Amazon S3. This allows for easy data cataloging with AWS Glue and seamless integration with QuickSight. Options A and B involve additional complexities and manual processes, while option D is less efficient due to the need for manual exports and uploads.