AWS Certified Data Engineer Associate DEA-C01 Practice Question
A company needs to ingest hourly updates from a third-party SaaS application that exposes a REST API protected by OAuth 2.0. The data must be stored as raw JSON objects in an Amazon S3 bucket. The solution should minimize code maintenance while automatically handling API token refresh and incremental retrieval. Which solution meets these requirements?
Configure an Amazon EventBridge rule to invoke an AWS Lambda function every hour; have the function obtain an OAuth token, call the API, and write the response to Amazon S3.
Provision an Amazon EC2 instance with a cron job that runs a Python script hourly to call the API and upload the data to Amazon S3.
Develop an AWS Glue Spark job that calls the REST API with a Python library, refreshes the OAuth token, and writes the data to Amazon S3; trigger the job hourly with an AWS Glue workflow.
Create an AWS AppFlow flow that uses a custom connector for the SaaS API, schedule it to run hourly, and configure Amazon S3 as the destination.
AWS AppFlow provides managed connectors for many SaaS applications and can also use custom connectors for any REST API that supports OAuth 2.0. AppFlow automatically handles token exchange and refresh, supports change-data capture and incremental transfer, and can deliver the records directly to Amazon S3 on a schedule as short as every hour. The other options require the data engineer to write and maintain code to manage OAuth tokens, error handling, and scheduling, which increases operational effort and potential failure points.
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How does OAuth 2.0 token refresh work in AWS AppFlow?
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What are the advantages of storing raw JSON data in Amazon S3?
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What is AWS AppFlow, and how does it help with data integration?
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How does OAuth 2.0 enable secure API calls?
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What are the benefits of storing data in Amazon S3 as raw JSON objects?
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AWS Certified Data Engineer Associate DEA-C01
Data Ingestion and Transformation
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