DEA-C01 Data Store Management Practice Question
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?
⚠ Common exam trap
Candidates often confuse maintenance commands (ANALYZE, VACUUM) with design changes, or think scaling out (adding nodes) is allowed when the question explicitly forbids changing cluster configuration.
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
✓
Redesign tables with appropriate sort keys and distribution styles.
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.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Increase the number of nodes in the cluster.
Why it's wrong here
This changes the cluster configuration, which is not allowed per the question.
- ✓
Redesign tables with appropriate sort keys and distribution styles.
Why this is correct
Proper sort keys and distribution can minimize data scanning and reduce I/O.
- ✗
Run the ANALYZE command to update table statistics.
Why it's wrong here
ANALYZE updates statistics but does not reduce I/O.
- ✗
Run the VACUUM command to reclaim disk space.
Why it's wrong here
Vacuum reclaims space but does not reduce I/O for queries.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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