The answer is to define sort keys on columns used in WHERE clauses, apply columnar compression, and choose an appropriate distribution style. Sort keys are correct because they enable Redshift’s zone maps to skip entire disk blocks that don’t match filter conditions, drastically reducing I/O for large fact tables. Columnar compression further shrinks storage and speeds scans by encoding similar data values efficiently, while a well-chosen distribution style—like KEY on a join column—minimizes data shuffling during joins with dimension tables. On the AWS Certified Data Engineer Associate DEA-C01 exam, this question tests your understanding of how physical table design directly impacts Redshift’s massively parallel processing architecture; a common trap is to focus only on indexing or caching, which Redshift does not use. Remember the mnemonic “Sort, Squeeze, Spread”—sort keys for pruning, compression for squeezing data, and distribution for spreading work across nodes.
DEA-C01 Data Store Management Practice Question
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 is using Amazon Redshift for its data warehouse. The data engineering team needs to improve query performance for a large fact table that is frequently joined with multiple dimension tables. Which THREE strategies should be considered?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Define sort keys on columns used in WHERE clauses.
Option A is correct because defining sort keys on columns used in WHERE clauses allows Amazon Redshift to use zone maps to skip large blocks of data that do not satisfy the filter condition, dramatically reducing the amount of data scanned. This is especially effective for large fact tables where selective filters can prune entire disk blocks, improving query performance without additional hardware.
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.
✓
Define sort keys on columns used in WHERE clauses.
Why this is correct
Improves filter efficiency.
Related concept
Read the scenario before looking for a memorised answer.
✗
Use DISTSTYLE EVEN to distribute data evenly.
Why it's wrong here
EVEN distribution does not optimize joins.
✗
Increase the number of nodes in the cluster.
Why it's wrong here
Scaling is costly and may not address root cause.
✓
Choose an appropriate distribution key based on join columns.
Why this is correct
Reduces data movement during joins.
Related concept
Read the scenario before looking for a memorised answer.
✓
Apply columnar compression to reduce storage and I/O.
Why this is correct
Compression reduces data scanned.
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 often assume DISTSTYLE EVEN is always the best choice for performance, but for frequently joined fact tables, a distribution key aligned with the join columns is critical to avoid network-heavy data shuffling.
Detailed technical explanation
How to think about this question
Under the hood, Amazon Redshift stores data in 1 MB blocks and uses zone maps (min/max values) for each block based on the sort key. When a WHERE clause filters on the sort key column, Redshift can skip entire blocks that fall outside the filter range, reducing I/O. For joins, choosing a distribution key that matches the join columns ensures data is co-located on the same node slice, avoiding expensive broadcast or redistribution operations that can dominate query execution time.
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.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Data Store Management — This question tests Data Store Management — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Define sort keys on columns used in WHERE clauses. — Option A is correct because defining sort keys on columns used in WHERE clauses allows Amazon Redshift to use zone maps to skip large blocks of data that do not satisfy the filter condition, dramatically reducing the amount of data scanned. This is especially effective for large fact tables where selective filters can prune entire disk blocks, improving query performance without additional hardware.
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.
About these practice questions
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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 uses Amazon Redshift for data warehousing. The data engineering team notices that queries are slow due to high disk I/O. The team wants to improve query performance without changing the cluster configuration. Which action should the team take?
medium
A.Increase the number of nodes in the cluster.
✓ B.Redesign tables with appropriate sort keys and distribution styles.
C.Run the ANALYZE command to update table statistics.
D.Run the VACUUM command to reclaim disk space.
Why B: Redesigning tables with appropriate sort keys and distribution styles directly addresses high disk I/O by minimizing data scanning and reducing data movement across nodes. Sort keys enable Redshift to skip irrelevant blocks via zone maps, while distribution styles (KEY, ALL, EVEN) optimize data locality for joins and aggregations, reducing I/O without changing cluster configuration.
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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.
Question Discussion
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