- A
Use COPY with compression (gzip) to reduce data volume.
Why wrong: Compression helps storage but not load time significantly.
- B
Use a VPC endpoint to improve network throughput to S3.
Why wrong: Network improvements are marginal; parallelism is key.
- C
Change the table distribution style to EVEN to distribute data evenly.
Why wrong: Distribution style affects query performance, not load speed.
- D
Increase the number of nodes in the Redshift cluster and use parallel COPY from multiple files.
More nodes enable parallel data loading.
Question 628 of 1,786
How to Speed Up Redshift COPY Loads with Parallelism and More Nodes
This DEA-C01 practice question tests your understanding of data ingestion and transformation. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. 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 is migrating its on-premises data warehouse to Amazon Redshift. The daily batch load from the source database takes 6 hours using a single-node Redshift cluster. The engineer needs to reduce load time to under 2 hours without increasing cost significantly. Which strategy should the engineer adopt?
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
✓
Increase the number of nodes in the Redshift cluster and use parallel COPY from multiple files.
Option D is correct because increasing the number of nodes in the Redshift cluster provides more compute and I/O capacity, and using parallel COPY from multiple files allows Redshift to automatically split the load across the node slices, dramatically reducing load time. This approach scales performance linearly with the number of nodes, enabling the engineer to meet the sub-2-hour target without significantly increasing cost if the cluster is sized appropriately.
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 COPY with compression (gzip) to reduce data volume.
Why it's wrong here
Compression helps storage but not load time significantly.
- ✗
Use a VPC endpoint to improve network throughput to S3.
Why it's wrong here
Network improvements are marginal; parallelism is key.
- ✗
Change the table distribution style to EVEN to distribute data evenly.
Why it's wrong here
Distribution style affects query performance, not load speed.
- ✓
Increase the number of nodes in the Redshift cluster and use parallel COPY from multiple files.
Why this is correct
More nodes enable parallel data loading.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates assume compression or network optimizations are the primary bottleneck, when in reality the single-node Redshift cluster's lack of parallelism is the root cause of the slow load time.
Detailed technical explanation
How to think about this question
Amazon Redshift uses a massively parallel processing (MPP) architecture where data is distributed across node slices. The COPY command automatically loads data in parallel from multiple files into these slices; with a single node, there is only one slice, limiting parallelism. Increasing the node count adds more slices, allowing the COPY command to leverage concurrent I/O and CPU resources, which directly reduces load time. The optimal number of files should be a multiple of the number of slices (e.g., 2 files per slice) to maximize parallelism.
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 startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.
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: Increase the number of nodes in the Redshift cluster and use parallel COPY from multiple files. — Option D is correct because increasing the number of nodes in the Redshift cluster provides more compute and I/O capacity, and using parallel COPY from multiple files allows Redshift to automatically split the load across the node slices, dramatically reducing load time. This approach scales performance linearly with the number of nodes, enabling the engineer to meet the sub-2-hour target without significantly increasing cost if the cluster is sized appropriately.
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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