This DP-203 practice question tests your understanding of design and implement data storage. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. 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 financial services company is migrating its data warehouse to Azure Synapse Analytics. They have a star schema with a 10-billion-row fact table and 50 dimension tables. Query performance is critical, and they need to minimize data movement during joins. Which distribution strategy should they use for the fact table?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue: "minimum / minimize"
Why it matters: Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.
Replicated distribution
Why wrong: Not suitable for large fact tables.
Partitioned distribution
Why wrong: Not a valid distribution strategy.
Hash distribution on the most frequently joined dimension key
Collocates data for joins.
Round-robin distribution
Why wrong: Causes data movement during joins.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
Hash distribution on the most frequently joined dimension key
Hash distribution on the most frequently joined dimension key is correct because it co-locates matching rows from the fact and dimension tables on the same compute node, minimizing data movement during joins. For a 10-billion-row fact table, this distribution ensures that the most common join operation is performed locally without shuffling data across nodes, which is critical for query performance in Azure Synapse Analytics.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
Replicated distribution
Why it's wrong here
Not suitable for large fact tables.
Partitioned distribution
Why it's wrong here
Not a valid distribution strategy.
Hash distribution on the most frequently joined dimension key
Why this is correct
Collocates data for joins.
Clue confirmation
The clue word "minimum / minimize" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
Round-robin distribution
Why it's wrong here
Causes data movement during joins.
Common exam traps
The trap here is that candidates confuse table partitioning with distribution strategy, assuming 'partitioned distribution' is a valid option, but Azure Synapse Analytics uses hash, round-robin, and replicated distributions only, while partitioning is a separate concept for data organization within a distribution.
Detailed technical explanation
Hash distribution uses a hash function on the distribution column to deterministically assign rows to distributions (60 distributions per database by default). When the fact table is hash-distributed on the same column as a dimension table, rows with the same key value land on the same distribution, enabling local hash joins without data movement. In real-world scenarios, choosing a column with high cardinality and frequent join usage is essential to avoid data skew, which can cause uneven distribution and bottleneck performance.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
An e-commerce site experiences heavy traffic on Black Friday and near-zero traffic during off-peak weeks. Rather than provisioning permanent large VMs, the team uses auto-scaling groups that add capacity automatically under load and reduce it overnight. Questions like this test whether you understand elasticity, availability zones, and cloud compute scaling patterns.
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FAQ
Design and implement data storage — This question tests Design and implement data storage — Read the scenario before looking for a memorised answer..
The correct answer is: Hash distribution on the most frequently joined dimension key — Hash distribution on the most frequently joined dimension key is correct because it co-locates matching rows from the fact and dimension tables on the same compute node, minimizing data movement during joins. For a 10-billion-row fact table, this distribution ensures that the most common join operation is performed locally without shuffling data across nodes, which is critical for query performance in Azure Synapse Analytics.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Yes — watch for: "minimum / minimize". Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 24, 2026
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