DP-203 Design and implement data storage Practice Question
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.
You are migrating an on-premises SQL Server database to Azure. The database has a large fact table (500 GB) and several dimension tables (10 GB total). Reporting queries join the fact table with dimension tables and aggregate by date. Which Azure service and table design should you recommend to minimize query latency?
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.
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Azure Synapse SQL Pool with hash distribution on the fact table's foreign key and round-robin for dimension tables
Option C is correct because Azure Synapse SQL Pool with hash distribution on the fact table's foreign key ensures that related rows from the fact and dimension tables are co-located on the same compute node, minimizing data movement during joins. Round-robin distribution for the small dimension tables is appropriate since they are under 1 GB each and can be broadcast to all nodes, further reducing shuffle overhead. This design optimizes parallel query execution for large fact table aggregations by date.
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.
✗
Azure Synapse SQL Pool with replicated tables for both fact and dimension tables
Why it's wrong here
Replicating large fact tables is not feasible due to storage and overhead.
✗
Azure SQL Database Hyperscale with columnstore indexes
Why it's wrong here
Hyperscale is for OLTP workloads, not data warehousing.
✓
Azure Synapse SQL Pool with hash distribution on the fact table's foreign key and round-robin for dimension tables
Why this is correct
Hash distribution enables co-location joins, improving query performance.
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.
✗
Azure SQL Database with rowstore indexes and a single database
Why it's wrong here
Azure SQL DB is not designed for large fact tables with heavy aggregation queries.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse replicated tables as a universal performance booster, not realizing that replicating a large fact table is impractical and that hash distribution on the join key is the correct pattern for large fact tables in a distributed MPP environment.
Detailed technical explanation
How to think about this question
Hash distribution uses a deterministic hash function on the distribution column (e.g., the foreign key) to assign rows to one of 60 distributions, ensuring that all rows with the same key value land on the same node. When joining fact and dimension tables on that key, the dimension table can be broadcast (if small) or hash-distributed to match, avoiding expensive data movement across nodes. In practice, if the fact table's foreign key has high cardinality and even data skew, hash distribution provides near-linear scale-out performance for aggregation queries.
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
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.
Related glossary terms
Concepts from this question explained
These glossary pages explain the core terms tested in this DP-203 question in full detail.
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: Azure Synapse SQL Pool with hash distribution on the fact table's foreign key and round-robin for dimension tables — Option C is correct because Azure Synapse SQL Pool with hash distribution on the fact table's foreign key ensures that related rows from the fact and dimension tables are co-located on the same compute node, minimizing data movement during joins. Round-robin distribution for the small dimension tables is appropriate since they are under 1 GB each and can be broadcast to all nodes, further reducing shuffle overhead. This design optimizes parallel query execution for large fact table aggregations by date.
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: "minimum / minimize". Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.
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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