- A
Create a non-clustered index on OrderDate and CustomerID
Correct. A non-clustered index on the columns used in WHERE clauses (OrderDate, CustomerID) allows the database engine to quickly locate rows without scanning the entire table.
- B
Create a clustered index on OrderDate
Why wrong: Incorrect. Changing the clustered index to OrderDate might help range queries on OrderDate but could disrupt other queries that rely on OrderID for sorting or joins. Also, it does not directly help with CustomerID filters.
- C
Create a non-clustered index on OrderID
Why wrong: Incorrect. OrderID is already the clustered index key, so the data is physically ordered by OrderID. An additional non-clustered index on OrderID would add overhead without benefit for OrderDate/CustomerID queries.
- D
Partition the table by CustomerID
Why wrong: Incorrect. Partitioning can improve management and possibly query performance for large tables, but without appropriate indexes, queries still need to scan partitions. An index on the filter columns is more effective for these specific queries.
DP-900 Practice Question: Identify considerations for relational data on Azure
This DP-900 practice question tests your understanding of identify considerations for relational data on azure. 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 company uses Azure SQL Database for an order management system. The 'Orders' table has millions of rows and is queried frequently with filters on OrderDate and CustomerID. The table currently has a clustered index on OrderID. Which action will most improve query performance for these frequent filters?
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
Create a non-clustered index on OrderDate and CustomerID
The frequent filters on OrderDate and CustomerID require a covering index that includes both columns. A non-clustered index on (OrderDate, CustomerID) allows SQL Server to perform an index seek for queries filtering on those columns, avoiding full clustered index scans on the existing clustered index on OrderID. This directly reduces I/O and improves query response times.
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.
- ✓
Create a non-clustered index on OrderDate and CustomerID
Why this is correct
Correct. A non-clustered index on the columns used in WHERE clauses (OrderDate, CustomerID) allows the database engine to quickly locate rows without scanning the entire table.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Create a clustered index on OrderDate
Why it's wrong here
Incorrect. Changing the clustered index to OrderDate might help range queries on OrderDate but could disrupt other queries that rely on OrderID for sorting or joins. Also, it does not directly help with CustomerID filters.
- ✗
Create a non-clustered index on OrderID
Why it's wrong here
Incorrect. OrderID is already the clustered index key, so the data is physically ordered by OrderID. An additional non-clustered index on OrderID would add overhead without benefit for OrderDate/CustomerID queries.
- ✗
Partition the table by CustomerID
Why it's wrong here
Incorrect. Partitioning can improve management and possibly query performance for large tables, but without appropriate indexes, queries still need to scan partitions. An index on the filter columns is more effective for these specific queries.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often assume partitioning alone solves query performance issues, but without an appropriate index, partitioning only helps with data management and partition elimination, not with efficient row-level filtering for specific column combinations.
Detailed technical explanation
How to think about this question
Under the hood, a non-clustered index on (OrderDate, CustomerID) creates a B-tree structure where the leaf pages contain the index key columns plus the clustered index key (OrderID) as a row locator. This enables SQL Server to perform an index seek with a key lookup only when additional columns are needed, but if the query only selects columns covered by the index, it can be satisfied entirely from the non-clustered index (covering index scenario). In real-world scenarios, this index can reduce query cost from millions of logical reads to just a few dozen.
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
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FAQ
Questions learners often ask
What does this DP-900 question test?
Identify considerations for relational data on Azure — This question tests Identify considerations for relational data on Azure — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Create a non-clustered index on OrderDate and CustomerID — The frequent filters on OrderDate and CustomerID require a covering index that includes both columns. A non-clustered index on (OrderDate, CustomerID) allows SQL Server to perform an index seek for queries filtering on those columns, avoiding full clustered index scans on the existing clustered index on OrderID. This directly reduces I/O and improves query response times.
What should I do if I get this DP-900 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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Last reviewed: Jun 11, 2026
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