The answer is hash distribution on CustomerID. This is correct because for a large partitioned fact table in Azure Synapse Dedicated SQL Pool, hash distribution on the join and filter key—CustomerID—ensures that rows with the same CustomerID are colocated on the same distribution node, while the date-based partitioning allows partition elimination to occur locally within each node, minimizing data movement during queries that filter on both CustomerID and Date. On the DP-203 exam, this scenario tests your understanding of how distribution strategy interacts with partitioning: a common trap is choosing round-robin (which scatters data and causes shuffles) or hash on Date (which undermines partition pruning). Remember the memory tip: “Hash the high-cardinality filter key, partition the time-based range.” This pairs distribution for collocation with partitioning for elimination, keeping data movement low and performance high.
DP-203 Develop data processing Practice Question
This DP-203 practice question tests your understanding of develop data processing. 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 partitioning a large fact table in Azure Synapse Dedicated SQL Pool by date. The table is used for queries that filter on CustomerID and Date. You want to minimize data movement. Which distribution strategy should you use?
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
✓
Hash distribution on CustomerID
Hash distribution on CustomerID is correct because queries filtering on CustomerID and Date will benefit from collocated joins and aggregations when CustomerID is the distribution key. Since the table is large and partitioned by Date, hash distribution on CustomerID minimizes data movement by ensuring that rows with the same CustomerID reside on the same distribution node, allowing filters on Date to be applied locally within each partition.
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.
✗
Round-robin distribution
Why it's wrong here
Round-robin distributes randomly; queries joining on CustomerID would cause data movement.
✓
Hash distribution on CustomerID
Why this is correct
Hash distribution on CustomerID ensures collocation for joins on that key, reducing data movement.
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.
✗
Replicate distribution
Why it's wrong here
Replicate is for small dimension tables, not large fact tables.
✗
Hash distribution on Date
Why it's wrong here
Hash on Date would be less effective for joins on CustomerID.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often assume partitioning and distribution should be on the same column (Date) to optimize date-range queries, but this ignores that distribution on the join key (CustomerID) is what minimizes data movement for the most common query pattern involving both CustomerID and Date filters.
Detailed technical explanation
How to think about this question
In Azure Synapse Dedicated SQL Pool, hash distribution uses a deterministic hash function on the distribution column to assign rows to one of 60 distributions. When a large fact table is partitioned by Date, each partition is further distributed across nodes; hash distribution on CustomerID ensures that all rows for a given CustomerID land on the same distribution, enabling partition-elimination and collocated joins without shuffling data across the control node. This design is critical for star-schema fact tables where CustomerID is a foreign key to a dimension table, as it avoids expensive data movement during joins and aggregations.
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.
Related glossary terms
Concepts from this question explained
These glossary pages explain the core terms tested in this DP-203 question in full detail.
Develop data processing — This question tests Develop data processing — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Hash distribution on CustomerID — Hash distribution on CustomerID is correct because queries filtering on CustomerID and Date will benefit from collocated joins and aggregations when CustomerID is the distribution key. Since the table is large and partitioned by Date, hash distribution on CustomerID minimizes data movement by ensuring that rows with the same CustomerID reside on the same distribution node, allowing filters on Date to be applied locally within each partition.
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.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
Share a tip, memory trick, or ask about the reasoning behind this question. Do not post real exam questions, leaked content, braindumps, or copyrighted exam material. Comments are moderated and may be removed without notice.
This DP-203 practice question is part of Courseiva's free Microsoft certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the DP-203 exam.
Question Discussion
Share a tip, memory trick, or ask about the reasoning behind this question. Do not post real exam questions, leaked content, braindumps, or copyrighted exam material. Comments are moderated and may be removed without notice.
Sign in to join the discussion.