- A
The fact_sales table uses clustered columnstore index.
Why wrong: Columnstore index does not cause shuffle.
- B
The dim_product table is replicated, causing a broadcast join.
Why wrong: Replicated tables are broadcast to all distributions, avoiding shuffle.
- C
Statistics are out of date on both tables.
Why wrong: Outdated statistics affect cardinality estimates but not directly shuffle.
- D
The join condition does not include the distribution key for fact_sales.
Joins on non-distribution keys require data movement.
DP-203 Design and implement data storage Practice Question
This DP-203 practice question tests your understanding of design and implement data storage. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. 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.
You are tuning a dedicated SQL pool in Azure Synapse Analytics. A query that joins two large tables (fact_sales and dim_product) is slow. The fact_sales table is hash-distributed on product_id, and dim_product is replicated. You notice that the query plan shows a shuffle move. What is the most likely cause?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue:
"most likely"Why it matters: Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
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
The join condition does not include the distribution key for fact_sales.
Option D is correct because when the join condition does not include the distribution key (product_id) of the hash-distributed fact_sales table, the SQL engine cannot perform a collocated join. Instead, it must shuffle data across distributions to satisfy the join, which introduces expensive data movement. The shuffle move in the query plan directly indicates this redistribution.
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.
- ✗
The fact_sales table uses clustered columnstore index.
Why it's wrong here
Columnstore index does not cause shuffle.
- ✗
The dim_product table is replicated, causing a broadcast join.
Why it's wrong here
Replicated tables are broadcast to all distributions, avoiding shuffle.
- ✗
Statistics are out of date on both tables.
Why it's wrong here
Outdated statistics affect cardinality estimates but not directly shuffle.
- ✓
The join condition does not include the distribution key for fact_sales.
Why this is correct
Joins on non-distribution keys require data movement.
Clue confirmation
The clue word "most likely" in the question point toward this answer.
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 confuse a shuffle move with a broadcast join or blame indexing, but the root cause is the mismatch between the join key and the distribution key, which forces data movement regardless of other optimizations.
Detailed technical explanation
How to think about this question
In Azure Synapse dedicated SQL pools, hash-distributed tables distribute rows across 60 distributions based on a hash of the distribution key. For a collocated join, both tables must be distributed on the same join key, or one table must be replicated. When the join condition omits the distribution key, the engine must redistribute one or both tables via a shuffle (e.g., a 'ShuffleMove' or 'BroadcastMove' in the plan), which involves network I/O and serialization overhead. This is a common performance bottleneck in MPP architectures.
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.
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FAQ
Questions learners often ask
What does this DP-203 question test?
Design and implement data storage — This question tests Design and implement data storage — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: The join condition does not include the distribution key for fact_sales. — Option D is correct because when the join condition does not include the distribution key (product_id) of the hash-distributed fact_sales table, the SQL engine cannot perform a collocated join. Instead, it must shuffle data across distributions to satisfy the join, which introduces expensive data movement. The shuffle move in the query plan directly indicates this redistribution.
What should I do if I get this DP-203 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Are there clue words in this question I should notice?
Yes — watch for: "most likely". Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 24, 2026
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