- A
AWS Data Pipeline
Why wrong: Data Pipeline is an older service; AppFlow is more modern for SaaS ingestion.
- B
AWS Glue
Why wrong: Glue can be used but requires more configuration than AppFlow for SaaS sources.
- C
Amazon Kinesis Data Firehose
Why wrong: Firehose is for streaming data, not for batch extraction from SaaS APIs.
- D
Amazon AppFlow
AppFlow is designed to ingest data from SaaS applications to S3 with minimal code.
Question 1,531 of 1,786
Which AWS Service Ingests SaaS Data with Minimal Code?
This DEA-C01 practice question tests your understanding of data ingestion and transformation. This is a configuration task: choose the command set that satisfies every stated requirement. Small differences — like 'secret' vs 'password' or 'transport input ssh' vs 'all' — change whether the answer is correct. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A company needs to ingest data from multiple SaaS applications (e.g., Salesforce, Marketo) into Amazon S3 for analytics. The data sources have different schemas and update frequencies. Which AWS service should be used to build this ingestion pipeline with minimal code?
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 (Option D) is the correct answer because it is purpose-built for ingesting data from SaaS applications like Salesforce and Marketo into Amazon S3 with minimal code. It supports various source connectors, handles schema variations, and allows scheduling based on update frequencies. AWS Data Pipeline (A) requires more manual configuration and code for connectors. AWS Glue (B) has connectors but is more complex for this use case, often requiring additional ETL scripting. Amazon Kinesis Data Firehose (C) is designed for streaming data, not batch extraction from SaaS APIs.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
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 Data Pipeline
Why it's wrong here
Data Pipeline is an older service; AppFlow is more modern for SaaS ingestion.
- ✗
AWS Glue
Why it's wrong here
Glue can be used but requires more configuration than AppFlow for SaaS sources.
- ✗
Amazon Kinesis Data Firehose
Why it's wrong here
Firehose is for streaming data, not for batch extraction from SaaS APIs.
- ✓
Amazon AppFlow
Why this is correct
AppFlow is designed to ingest data from SaaS applications to S3 with minimal code.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Detailed technical explanation
How to think about this question
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
- Use explanations to understand the rule behind the answer.
TExam Day Tips
- Underline the problem statement mentally.
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
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 |
What to study next
Got this wrong? Here's your next step.
Identify which DEA-C01 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
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Data Ingestion and Transformation — study guide chapter
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FAQ
Questions learners often ask
What does this DEA-C01 question test?
Data Ingestion and Transformation — This question tests Data Ingestion and Transformation — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Amazon AppFlow — Amazon AppFlow (Option D) is the correct answer because it is purpose-built for ingesting data from SaaS applications like Salesforce and Marketo into Amazon S3 with minimal code. It supports various source connectors, handles schema variations, and allows scheduling based on update frequencies. AWS Data Pipeline (A) requires more manual configuration and code for connectors. AWS Glue (B) has connectors but is more complex for this use case, often requiring additional ETL scripting. Amazon Kinesis Data Firehose (C) is designed for streaming data, not batch extraction from SaaS APIs.
What should I do if I get this DEA-C01 question wrong?
Identify which DEA-C01 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
Same concept, more angles
4 more ways this is tested on DEA-C01
These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. A company needs to ingest data from multiple SaaS applications (e.g., Salesforce, Marketo) into Amazon S3 for centralized analytics. The data volume is several GB per day. Which AWS service is most suitable for this ingestion?
easy- A.Amazon Kinesis Data Firehose
- ✓ B.AWS Glue
- C.Amazon Athena
- D.AWS Data Pipeline
Why B: AWS Glue is the most suitable service because it provides a fully managed ETL (Extract, Transform, Load) capability with built-in connectors for SaaS applications like Salesforce and Marketo. Glue can extract data from these sources, transform it as needed, and write it to Amazon S3, handling the several GB per day volume efficiently without requiring custom code for each source.
Variation 2. A company needs to ingest data from multiple SaaS applications into Amazon S3. The data sources provide REST APIs. Which AWS service can be used to build a fully managed data ingestion pipeline without writing custom code?
easy- ✓ A.Amazon AppFlow
- B.Amazon Kinesis Data Streams
- C.AWS Lambda with custom code
- D.AWS Glue with Python shell
Why A: Option A is correct because Amazon AppFlow is a fully managed service designed to transfer data from SaaS applications to AWS services like Amazon S3 without writing custom code. Option B is wrong because Amazon Kinesis Data Streams is primarily for real-time streaming data, not for directly ingesting from SaaS APIs. Option C is wrong because AWS Lambda requires custom code to integrate with SaaS APIs. Option D is wrong because AWS Glue with Python shell is for ETL transformations and also requires custom scripting.
Variation 3. A company wants to ingest data from multiple SaaS applications into Amazon S3 using a fully managed service that supports schema discovery and transformation. Which AWS service should they use?
easy- A.Amazon Kinesis Data Firehose
- ✓ B.Amazon AppFlow
- C.AWS Glue
- D.AWS Data Pipeline
Why B: Option B is correct because Amazon AppFlow is a fully managed integration service that supports SaaS sources, schema discovery, and data transformation. Option A (Amazon Kinesis Data Firehose) is for streaming data but not for SaaS ingestion directly. Option C (AWS Glue) is an ETL service but not for SaaS ingestion directly. Option D (AWS Data Pipeline) is not fully managed for SaaS.
Variation 4. A company wants to ingest data from SaaS applications (e.g., Salesforce, Marketo) into Amazon S3 for analytics. The data volume is moderate and updates occur frequently. Which AWS service is BEST suited for this task?
medium- A.Amazon Kinesis Data Streams
- ✓ B.Amazon AppFlow
- C.AWS Database Migration Service (DMS)
- D.AWS Glue
Why B: Amazon AppFlow is specifically designed to securely transfer data from SaaS applications like Salesforce and Marketo to AWS services such as Amazon S3. It handles authentication, data transformation, and scheduling. Amazon Kinesis Data Streams is for real-time streaming data, not batch ingestion from SaaS. AWS Database Migration Service (DMS) is for migrating databases, not SaaS data. AWS Glue is an ETL service that can process data but is not optimized for direct SaaS ingestion.
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Last reviewed: Jun 20, 2026
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