DEA-C01 Data Ingestion and Transformation Practice Question
A data engineer needs to ingest data from multiple SaaS applications (Salesforce, Marketo) into Amazon S3 for a data lake. The data volumes are moderate and the sync needs to be scheduled daily. Which AWS service is most appropriate for this task?
⚠ Common exam trap
Many candidates confuse AWS Glue's ETL capabilities with direct SaaS ingestion, overlooking that Glue requires a custom connector or script to pull from APIs, whereas AppFlow provides native, managed connectors.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Amazon AppFlow
Amazon AppFlow is purpose-built for securely transferring data between SaaS applications (like Salesforce and Marketo) and AWS services (like S3). It supports scheduled, incremental data syncs with built-in connectors, making it the most appropriate choice for moderate-volume daily ingestion into a data lake.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
AWS Glue
Why it's wrong here
AWS Glue is a serverless ETL service for transforming and cataloguing data, and its connectors target databases and streams rather than native SaaS application APIs. It is tempting because it is the general-purpose AWS data-integration service. It would be correct for scheduled transformation jobs over data already in S3.
- ✓
Amazon AppFlow
Why this is correct
Amazon AppFlow provides managed connectors for SaaS sources such as Salesforce and Marketo, with scheduled flows delivering data into Amazon S3. It handles moderate volumes and daily synchronisation without custom ingestion code, matching the stated constraints.
- ✗
AWS Database Migration Service (DMS)
Why it's wrong here
AWS DMS migrates data between databases and data stores using replication instances, and it has no native Salesforce or Marketo source endpoints. It is tempting because it is a managed ingestion service. It would be correct for continuous replication from an on-premises or EC2-hosted relational database into S3.
- ✗
Amazon Kinesis Data Firehose
Why it's wrong here
Firehose performs continuous, near-real-time delivery of streaming records, not scheduled batch pulls from SaaS APIs; it cannot poll Salesforce or Marketo on a daily cadence. It is tempting because it loads streams into Amazon S3, which would be correct for high-volume, continuously produced event data rather than moderate daily syncs.
Quick reference
AWS S3 Storage Class Comparison
| Storage Class | Min Duration | Retrieval | Use Case |
|---|---|---|---|
| S3 Standard | None | Immediate | Frequently accessed data |
| S3 Standard-IA | 30 days | Immediate | Infrequent access, rapid retrieval |
| S3 One Zone-IA | 30 days | Immediate | Non-critical infrequent data |
| S3 Intelligent-Tiering | None | Immediate–hours | Unknown or changing access patterns |
| S3 Glacier Instant | 90 days | Milliseconds | Archive with instant retrieval |
| S3 Glacier Flexible | 90 days | Minutes–hours | Archive, flexible retrieval |
| S3 Glacier Deep Archive | 180 days | Hours | Long-term compliance archive |
Go deeper
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JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This DEA-C01 practice question is part of Courseiva's free Amazon Web Services certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the DEA-C01 exam.