DEA-C01 practice question 12 of 25

A company wants to combine data from multiple software as a service (SaaS) applications for analysis. A data engineering team needs to use Amazon…

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 Row 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. Correct answer

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. Use Amazon AppFlow to create a Row 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.

Explanation

Amazon AppFlow is a fully managed integration service specifically designed to securely transfer data between SaaS applications and AWS services with minimal effort. It provides pre-built connectors for numerous SaaS applications, eliminating the need to write and maintain custom API integration code. By creating a flow for each SaaS application with Amazon S3 as the destination, the data extraction can be scheduled and automated. This is the most operationally efficient solution as it is a no-code, managed service. Once the data is in S3, it can be cataloged with AWS Glue and easily consumed by Amazon QuickSight for analysis.

Why Incorrect

A. Creating custom AWS Lambda functions requires significant development, testing, and maintenance overhead for API integrations, making it less operationally efficient than a managed service like AppFlow.
B. Using Athena federated queries can be complex to set up and may not be performant for dashboarding, as it queries the source APIs in real-time. It is less efficient than landing data in S3.
D. Manually exporting data to Excel files is a highly manual, error-prone process that is not scalable or automated. It represents the highest operational effort among the options.

References

1. AWS Documentation. (2023). What Is Amazon AppFlow?. Amazon AppFlow User Guide. Retrieved from https://docs.aws.amazon.com/appflow/latest/userguide/what-is-appflow.html (The guide states, "Amazon AppFlow is a fully managed integration service that you can use to securely transfer data between Software-as-a-Service (SaaS) applications... and AWS services").

2. AWS Documentation. (2023). Supported source and destination applications. Amazon AppFlow User Guide. Retrieved from https://docs.aws.amazon.com/appflow/latest/userguide/apps.html (This page lists the pre-built connectors that reduce operational effort).

3. AWS Documentation. (2023). Using Amazon S3 as a destination. Amazon AppFlow User Guide. Retrieved from https://docs.aws.amazon.com/appflow/latest/userguide/s3.html (This describes the standard pattern of using AppFlow to land SaaS data in S3 for downstream analytics).

Keep practicing

Take the free DEA-C01 practice test

Ten exam-style questions with answers and explanations, plus the exam facts and study guides.

Start the free practice test