- A
Clustered index on (AccountID, TransactionDate)
Why wrong: Incorrect. The table already has a clustered index on TransactionID. Creating another clustered index is not allowed, and changing the clustered index would cause page reordering and impact other queries.
- B
Nonclustered index on (TransactionDate)
Why wrong: Incorrect. This index helps only for TransactionDate filters but does not efficiently narrow down by AccountID first.
- C
Nonclustered index on (AccountID) INCLUDE (TransactionDate)
Why wrong: Incorrect. This index can seek on AccountID but then requires a key lookup for each matching row to filter on TransactionDate, which is less efficient than a composite index.
- D
Nonclustered index on (AccountID, TransactionDate)
Correct. A composite nonclustered index on (AccountID, TransactionDate) enables an index seek on AccountID and a range scan on TransactionDate within that partition, minimizing I/O.
Quick Answer
The answer is a nonclustered composite index on (AccountID, TransactionDate). This is the most efficient strategy because it creates a covering index that matches the exact filter order of the queries, allowing SQL Server to perform a direct index seek rather than a full table scan or costly key lookups. On the Microsoft Azure Data Fundamentals DP-900 exam, this scenario tests your understanding of how composite indexes optimize multi-column filters, a common performance tuning concept for Azure SQL Database. A frequent trap is choosing separate single-column indexes, which forces the database to merge results inefficiently. Remember the memory tip: "first column for equality, second for range"—AccountID is typically filtered with equality, while TransactionDate often uses a range, making this composite order ideal for boosting queries on both columns together.
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 financial application stores transactions in an Azure SQL Database table with columns: TransactionID (clustered index), AccountID, TransactionDate, Amount. Queries frequently filter on AccountID and TransactionDate together. The table contains millions of rows. Which index strategy will most improve query performance for these 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
Nonclustered index on (AccountID, TransactionDate)
Option D creates a nonclustered index on (AccountID, TransactionDate) that acts as a covering index for queries filtering on both columns. SQL Server can seek directly to the matching rows using the composite key order, avoiding a full table scan or key lookup. This is the most efficient strategy because the index is sorted by AccountID first, then TransactionDate, matching the query predicate exactly.
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.
- ✗
Clustered index on (AccountID, TransactionDate)
Why it's wrong here
Incorrect. The table already has a clustered index on TransactionID. Creating another clustered index is not allowed, and changing the clustered index would cause page reordering and impact other queries.
- ✗
Nonclustered index on (TransactionDate)
Why it's wrong here
Incorrect. This index helps only for TransactionDate filters but does not efficiently narrow down by AccountID first.
- ✗
Nonclustered index on (AccountID) INCLUDE (TransactionDate)
Why it's wrong here
Incorrect. This index can seek on AccountID but then requires a key lookup for each matching row to filter on TransactionDate, which is less efficient than a composite index.
- ✓
Nonclustered index on (AccountID, TransactionDate)
Why this is correct
Correct. A composite nonclustered index on (AccountID, TransactionDate) enables an index seek on AccountID and a range scan on TransactionDate within that partition, minimizing I/O.
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 Option A (changing the clustered index) because they think it will be faster for all queries, but they overlook the negative impact on the existing primary key and the fact that a nonclustered covering index is sufficient and less disruptive.
Detailed technical explanation
How to think about this question
Under the hood, SQL Server's B-tree index structure allows a composite index to be used for seeks when the leading key column is specified in the WHERE clause. For queries filtering on both AccountID and TransactionDate, the index on (AccountID, TransactionDate) enables an index seek at the AccountID level, then a range or equality seek within that AccountID's subtree. In real-world scenarios, this index also supports queries that filter only on AccountID (due to the leftmost prefix rule), making it a versatile choice for mixed workloads.
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: Nonclustered index on (AccountID, TransactionDate) — Option D creates a nonclustered index on (AccountID, TransactionDate) that acts as a covering index for queries filtering on both columns. SQL Server can seek directly to the matching rows using the composite key order, avoiding a full table scan or key lookup. This is the most efficient strategy because the index is sorted by AccountID first, then TransactionDate, matching the query predicate exactly.
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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