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…

Question

Options

• ACreate AWS Lambda functions that call the required APIs to extract the data from the
• BUse AWS Lambda functions as Amazon Athena data source connectors to run federated queries
• CUse Amazon AppFlow to create a flow for each SaaS application. Set an Amazon S3 bucket as
• DExport data the from the SaaS applications as Microsoft Excel files. Create a data source and a

• A
  3% (1)
• B
  11% (4)
• C
  84% (32)
• D
  3% (1)

Explanation

Amazon AppFlow is a fully managed, no-code/low-code integration service with pre-built connectors for hundreds of SaaS applications (Salesforce, ServiceNow, Zendesk, etc.). You create a flow per SaaS source, set an S3 bucket as the destination, and schedule runs-no custom code required. QuickSight can then query the S3 data via Athena or direct S3 manifest. This is the most operationally efficient because no Lambda code needs to be written or maintained. Custom Lambda functions calling APIs (A) require writing API integration code, handling pagination, auth, and error handling. Lambda-based Athena federated query connectors (B) are better suited for direct query federation, not bulk extraction. Exporting to Excel files (D) is a manual, non-scalable process that defeats automation.

No community discussion yet for this question.