The correct answer is to recreate the table using hash distribution on CustomerID and use CTAS for incremental loads. Hash distribution on CustomerID ensures that rows with the same key are co-located on the same distribution node, which eliminates data movement during joins with the replicated DimCustomer table and dramatically improves query performance. This approach directly addresses the poor performance caused by the current round-robin distribution, which scatters data randomly and forces costly shuffles. On the DP-203 exam, this scenario tests your understanding of distribution strategies and incremental loading patterns—a common trap is choosing round-robin or replicated for large fact tables, which either causes excessive data movement or exceeds storage limits. Remember the memory tip: “Hash the join key, CTAS the load key”—hash distribution on the most-filtered column minimizes shuffling, while CTAS rebuilds the table efficiently without blocking reads, making it ideal for incremental updates.
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 a data engineer at a financial services company. The company uses Azure Synapse Analytics with a dedicated SQL pool for its data warehouse. The current table 'FactTransactions' is 2 TB and uses round-robin distribution. Query performance is poor for queries that frequently filter on 'CustomerID' and join with a 'DimCustomer' table (10 GB, replicated). You need to redesign the table to improve query performance while minimizing data movement during queries. The solution must also support incremental data loading with minimal overhead. You cannot change the storage size limit or add more DWU. What should you do?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Recreate the table using hash distribution on CustomerID and use CTAS for incremental loads.
Option D is correct because hash distribution on CustomerID ensures that rows with the same CustomerID are co-located on the same distribution, which eliminates data movement during joins with the replicated DimCustomer table. Using CTAS (CREATE TABLE AS SELECT) for incremental loads allows you to efficiently rebuild the table with minimal overhead by loading only new data into a staging table, then swapping partitions or using CTAS to replace the target table without blocking reads.
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.
✗
Replicate the FactTransactions table to all distributions.
Why it's wrong here
Table is too large to replicate; would exceed storage limits.
✗
Keep round-robin distribution but add indexes on CustomerID and TransactionDate.
Why it's wrong here
Does not collocate data for joins; still causes data movement.
✗
Change distribution to hash on TransactionDate and partition by month.
Why it's wrong here
Does not benefit join on CustomerID.
✓
Recreate the table using hash distribution on CustomerID and use CTAS for incremental loads.
Why this is correct
Collocates data on CustomerID, reducing data movement; CTAS handles incremental loads.
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 choose hash distribution on a date column (Option C) thinking it helps with time-based queries, but the question specifically requires improving join performance on CustomerID, so the distribution key must match the join key to avoid data movement.
Detailed technical explanation
How to think about this question
Hash distribution uses a deterministic hash function on the distribution column to assign rows to specific distributions, ensuring that all rows with the same CustomerID land on the same node. CTAS is a fully logged operation that can be used to create a new table with a different distribution or partition scheme, and it supports minimal logging when the target table is a heap or clustered columnstore index, making incremental loads efficient by loading into a staging table and then using ALTER TABLE SWITCH to move partitions.
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 media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
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: Recreate the table using hash distribution on CustomerID and use CTAS for incremental loads. — Option D is correct because hash distribution on CustomerID ensures that rows with the same CustomerID are co-located on the same distribution, which eliminates data movement during joins with the replicated DimCustomer table. Using CTAS (CREATE TABLE AS SELECT) for incremental loads allows you to efficiently rebuild the table with minimal overhead by loading only new data into a staging table, then swapping partitions or using CTAS to replace the target table without blocking reads.
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.
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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