Quick Answer
The answer is to use the COPY command to load data from Amazon S3. This is correct because Redshift is a massively parallel processing (MPP) data warehouse designed for bulk operations; the COPY command ingests data in parallel across all nodes, bypassing the per-row overhead of transaction logging and commit processing that plagues small INSERT statements. On the AWS Certified Data Engineer Associate DEA-C01 exam, this question tests your understanding of Redshift’s architecture and the principle that you should always favor batch loading over row-by-row operations to improve write performance. A common trap is choosing the multi-row INSERT or staging tables, but the COPY command remains the gold standard for efficient, scalable data ingestion. Memory tip: think “COPY = bulk, INSERT = bulk” — if you see small inserts, always COPY from S3.
This DEA-C01 practice question tests your understanding of data store management. 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 uses Amazon Redshift for analytics. The data engineer notices that queries are slow due to many small inserts. Which technique would improve write performance?
Use the COPY command to load data from Amazon S3.
Bulk loading is more efficient than small inserts.
Define DISTKEY and SORTKEY on the table.
Why wrong: These optimize queries, not inserts.
Increase the number of nodes in the cluster.
Why wrong: Scaling out doesn't optimize small inserts.
Configure workload management (WLM) queues.
Why wrong: WLM manages concurrency, not insert performance.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
Use the COPY command to load data from Amazon S3.
The COPY command is the recommended way to load data into Amazon Redshift because it performs bulk inserts in parallel across all nodes, leveraging the cluster's distributed architecture. Small individual INSERT statements cause high overhead due to transaction logging and commit processing, leading to slow write performance. By loading data from Amazon S3 using COPY, you bypass these per-row overheads and achieve optimal throughput.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
Use the COPY command to load data from Amazon S3.
Why this is correct
Bulk loading is more efficient than small inserts.
Related concept
Read the scenario before looking for a memorised answer.
Define DISTKEY and SORTKEY on the table.
Why it's wrong here
These optimize queries, not inserts.
Increase the number of nodes in the cluster.
Why it's wrong here
Scaling out doesn't optimize small inserts.
Configure workload management (WLM) queues.
Why it's wrong here
WLM manages concurrency, not insert performance.
Common exam traps
The trap here is that candidates often confuse performance tuning for reads (DISTKEY/SORTKEY) or general scaling (adding nodes) with the specific write performance bottleneck caused by many small inserts, overlooking the COPY command as the primary solution for bulk data loading.
Detailed technical explanation
Under the hood, each INSERT statement in Redshift triggers a transaction log write and a commit, which involves synchronous disk I/O and metadata updates. The COPY command, in contrast, loads data in large batches (default 1 MB per slice) using parallel streaming from S3, and automatically compresses and sorts data during load. A real-world scenario is ingesting streaming data: instead of inserting rows one by one, you batch them into files on S3 (e.g., every 5 minutes) and run COPY, dramatically reducing load time and avoiding table bloat from many small transactions.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
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.
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FAQ
Data Store Management — This question tests Data Store Management — Read the scenario before looking for a memorised answer..
The correct answer is: Use the COPY command to load data from Amazon S3. — The COPY command is the recommended way to load data into Amazon Redshift because it performs bulk inserts in parallel across all nodes, leveraging the cluster's distributed architecture. Small individual INSERT statements cause high overhead due to transaction logging and commit processing, leading to slow write performance. By loading data from Amazon S3 using COPY, you bypass these per-row overheads and achieve optimal throughput.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 24, 2026
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.
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