The answer is to run the ANALYZE command to refresh Redshift table statistics. This is correct because stale statistics prevent the Redshift query optimizer from accurately estimating row counts, leading to poor join orders and inefficient data scan strategies that degrade performance over time. The ANALYZE command updates these statistics, enabling the optimizer to generate optimal execution plans. On the AWS Certified Data Engineer Associate DEA-C01 exam, this tests your understanding of how the optimizer relies on fresh metadata for cost-based decisions; a common trap is confusing ANALYZE with VACUUM, which reclaims disk space but does not update statistics. Remember the memory tip: ANALYZE updates the optimizer’s “cheat sheet” for smarter query plans, while VACUUM cleans up the physical storage.
DEA-C01 Data Operations and Support Practice Question
This DEA-C01 practice question tests your understanding of data operations and support. 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 runs a Redshift cluster and notices that query performance has degraded over time. The data engineer suspects that table statistics are stale. What should the engineer do to improve query performance?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Run the ANALYZE command on the tables
Stale table statistics cause the Redshift query optimizer to generate suboptimal execution plans, leading to degraded query performance. Running the ANALYZE command updates these statistics, allowing the optimizer to make better decisions about join order, distribution, and data scan strategies. This directly addresses the root cause of performance degradation over time.
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.
✗
Rebuild the tables by using CREATE TABLE AS
Why it's wrong here
Rebuilding is heavy and not a standard fix for stale stats.
✗
Increase the number of slices in the cluster
Why it's wrong here
Slices are fixed per node type and not a performance tuning knob for stale stats.
✓
Run the ANALYZE command on the tables
Why this is correct
ANALYZE updates table statistics for the optimizer.
Related concept
Read the scenario before looking for a memorised answer.
✗
Run the VACUUM command on the tables
Why it's wrong here
VACUUM reclaims space but does not update statistics.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is confusing the VACUUM command (which reorganizes physical storage) with the ANALYZE command (which updates query optimizer metadata), leading candidates to choose VACUUM when stale statistics are the actual culprit.
Detailed technical explanation
How to think about this question
Redshift stores table statistics in the pg_statistic system catalog, which the query optimizer uses to estimate row counts, data distribution, and join selectivity. The ANALYZE command samples rows (default 100 rows per slice per table, configurable via the STATS threshold) and refreshes these catalog entries; without fresh statistics, the optimizer may choose nested loop joins over hash joins or misestimate filter selectivity, causing severe performance degradation even on well-distributed data.
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 cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
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 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: Run the ANALYZE command on the tables — Stale table statistics cause the Redshift query optimizer to generate suboptimal execution plans, leading to degraded query performance. Running the ANALYZE command updates these statistics, allowing the optimizer to make better decisions about join order, distribution, and data scan strategies. This directly addresses the root cause of performance degradation over time.
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.
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Question Discussion
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