- A
Use a different file format like Avro
Why wrong: Avro is not as efficient for pruning as Parquet.
- B
Ensure that the WHERE clause uses the partition column correctly
Enables partition pruning.
- C
Convert the data from Parquet to CSV for better compression
Why wrong: CSV is not columnar and would scan more data.
- D
Increase the number of partitions by adding a second partition column
Why wrong: More partitions may not help if the filter is not used.
- E
Enable predicate pushdown in Athena
Reduces data scanned by pushing filters to the storage layer.
Quick Answer
The answer is to enable predicate pushdown in Athena and ensure the partition column is used correctly in the WHERE clause. These two actions directly improve Athena partition pruning performance optimization by forcing the query engine to skip irrelevant S3 prefixes and read only the necessary Parquet files, dramatically reducing the data scanned. On the AWS Certified Data Engineer Associate DEA-C01 exam, this concept tests your understanding of how Athena’s distributed engine interacts with Hive-style partitioning and columnar storage—a common trap is assuming more partitions always help, when in fact a missing filter on the partition key renders pruning useless. Remember the memory tip: “Filter first, prune fast”—always verify your WHERE clause explicitly references the partition column, and pair Parquet’s built-in predicate pushdown with that filter to minimize scan volume.
DEA-C01 Data Operations and Support Practice Question
This DEA-C01 practice question tests your understanding of data operations and support. 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 runs a data lake on Amazon S3 with AWS Glue for ETL. The data is stored in Parquet format and partitioned by date. The data engineer notices that queries using Amazon Athena are scanning large amounts of data even when filtering on the partition column. Which TWO actions would improve query performance? (Choose TWO)
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
Ensure that the WHERE clause uses the partition column correctly
Option B and D are correct. Partition pruning is most effective when the partition column is used correctly in the WHERE clause, and using columnar formats like Parquet with predicate pushdown reduces data scanned. Option A is wrong because adding more partitions may not help if the filter is not applied. Option C is wrong because converting to CSV would increase data scanned. Option E is wrong because using a different file format may not help if partitioning is not leveraged.
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 a different file format like Avro
Why it's wrong here
Avro is not as efficient for pruning as Parquet.
- ✓
Ensure that the WHERE clause uses the partition column correctly
Why this is correct
Enables partition pruning.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Convert the data from Parquet to CSV for better compression
Why it's wrong here
CSV is not columnar and would scan more data.
- ✗
Increase the number of partitions by adding a second partition column
Why it's wrong here
More partitions may not help if the filter is not used.
- ✓
Enable predicate pushdown in Athena
Why this is correct
Reduces data scanned by pushing filters to the storage layer.
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.
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 Operations and Support — study guide chapter
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FAQ
Questions learners often ask
What does this DEA-C01 question test?
Data Operations and Support — This question tests Data Operations and Support — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Ensure that the WHERE clause uses the partition column correctly — Option B and D are correct. Partition pruning is most effective when the partition column is used correctly in the WHERE clause, and using columnar formats like Parquet with predicate pushdown reduces data scanned. Option A is wrong because adding more partitions may not help if the filter is not applied. Option C is wrong because converting to CSV would increase data scanned. Option E is wrong because using a different file format may not help if partitioning is not leveraged.
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.
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Last reviewed: Jun 20, 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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