- A
Use S3 Transfer Acceleration to speed up the transfer
Why wrong: Transfer Acceleration can help but not as much as multiple agents and compression.
- B
Use AWS Snowball Edge to transfer the data physically
Why wrong: Snowball is for large datasets or low bandwidth, but 10 TB over 1 Gbps can be done in ~22 hours, so Snowball may be unnecessary.
- C
Use AWS DataSync with multiple agents and enable data compression
Multiple agents and compression maximize throughput to meet the deadline.
- D
Request a bandwidth increase from the ISP
Why wrong: Bandwidth increase may not be possible in time.
Question 558 of 1,786
DEA-C01 Data Ingestion and Transformation Practice Question
This DEA-C01 practice question tests your understanding of data ingestion and transformation. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. 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 wants to migrate on-premises data to Amazon S3 using AWS DataSync. The data is 10 TB and the network bandwidth is 1 Gbps. The migration must be completed within 48 hours. What should the data engineer do to meet the deadline?
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
✓
Use AWS DataSync with multiple agents and enable data compression
Option C is correct because AWS DataSync can use multiple agents in parallel to increase throughput, and enabling data compression reduces the amount of data transferred over the network. With 10 TB at 1 Gbps, the theoretical minimum transfer time is about 22.2 hours, but real-world overhead (protocol, retransmissions) often exceeds 48 hours without parallelism and compression. Multiple agents and compression together can achieve the required throughput within the deadline.
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.
- ✗
Use S3 Transfer Acceleration to speed up the transfer
Why it's wrong here
Transfer Acceleration can help but not as much as multiple agents and compression.
- ✗
Use AWS Snowball Edge to transfer the data physically
Why it's wrong here
Snowball is for large datasets or low bandwidth, but 10 TB over 1 Gbps can be done in ~22 hours, so Snowball may be unnecessary.
- ✓
Use AWS DataSync with multiple agents and enable data compression
Why this is correct
Multiple agents and compression maximize throughput to meet the deadline.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Request a bandwidth increase from the ISP
Why it's wrong here
Bandwidth increase may not be possible in time.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates assume S3 Transfer Acceleration is a bandwidth booster, but it only reduces latency for small objects over long distances, not the total transfer time for large datasets constrained by bandwidth.
Detailed technical explanation
How to think about this question
AWS DataSync uses the S3 multipart upload API under the hood, and multiple agents can be deployed on separate EC2 instances or on-premises hosts to parallelize the transfer across different file sets. Data compression in DataSync uses gzip-level compression at the agent level, reducing the amount of data sent over the wire, which is especially effective for compressible data like logs or text files. In real-world scenarios, network bandwidth is often shared and not fully dedicated, so multiple agents and compression provide a buffer against variable throughput.
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.
TExam Day Tips
- 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.
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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: Use AWS DataSync with multiple agents and enable data compression — Option C is correct because AWS DataSync can use multiple agents in parallel to increase throughput, and enabling data compression reduces the amount of data transferred over the network. With 10 TB at 1 Gbps, the theoretical minimum transfer time is about 22.2 hours, but real-world overhead (protocol, retransmissions) often exceeds 48 hours without parallelism and compression. Multiple agents and compression together can achieve the required throughput within the deadline.
What should I do if I get this DEA-C01 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jul 4, 2026
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