DEA-C01 Data Store Management Practice Question
A data engineer is troubleshooting an Amazon Redshift cluster that is running out of disk space. The engineer runs STV_PARTITIONS and notices that some slices have significantly more data than others. What is the most likely cause and solution?
⚠ Common exam trap
Many candidates confuse sort keys (which improve query performance via zone maps) with distribution keys (which control data placement across slices), leading them to incorrectly select sort key redefinition as the fix for disk space skew.
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
✓
Data distribution skew due to uneven distribution style; change distribution style to EVEN or correct KEY
B is correct because STV_PARTITIONS shows per-slice disk usage, and significant variation indicates data distribution skew. Uneven distribution causes some slices to fill faster, leading to premature disk-full errors. Changing the distribution style to EVEN (for tables without join keys) or correcting the KEY distribution style (using a high-cardinality, evenly distributed column) rebalances data across slices.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Poorly chosen sort keys; redefine sort keys
Why it's wrong here
Sort keys affect query performance, not data distribution.
- ✓
Data distribution skew due to uneven distribution style; change distribution style to EVEN or correct KEY
Why this is correct
Uneven distribution can cause some slices to fill up faster.
- ✗
Some nodes are underutilized; add more nodes
Why it's wrong here
Adding nodes does not fix skew; it may mask the issue.
- ✗
Concurrency scaling is disabled; enable concurrency scaling
Why it's wrong here
Concurrency scaling handles read queries, not storage.
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Written by Johnson Ajibi, MSc IT Security
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