Question 477 of 982

Identify considerations for relational data on Azure →hardMultiple ChoiceObjective-mapped

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 has an Azure SQL Database with an 'Orders' table containing millions of rows. The table has a clustered index on OrderID (primary key). Queries frequently filter by CustomerID (equality) and OrderDate (range). These queries are slow and cause high logical reads. Which index strategy will most improve performance for these specific queries?

Clue words in this question

Noticing these words before you look at the options changes how you read each choice.

Clue: "primary"
Why it matters: Asks for the main purpose or function, not a secondary benefit. Eliminate answers that describe side-effects or partial functions.

Question 1hardmultiple choice

Full question →

A
Create a non-clustered index on (CustomerID, OrderDate).
This composite index matches the query pattern exactly: it allows index seek on CustomerID and then range scan on OrderDate, providing optimal performance.
B
Rebuild the clustered index on (OrderDate, CustomerID).
Why wrong: Changing the clustered index would rearrange the entire table, potentially harming other queries that rely on OrderID ordering. It is a major change with broader impact and may not be the best first approach.
C
Create a non-clustered index on OrderDate.
Why wrong: This index would require filtering on CustomerID separately, likely leading to many key lookups and still high reads. It is not as efficient as a composite covering index.
D
Create a filtered index on OrderDate for recent dates.
Why wrong: A filtered index would only benefit queries restricted to the filtered condition (e.g., recent dates) and would not help for historical range queries. It is too narrow in scope.

Full breakdown with real-world context →

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 (CustomerID, OrderDate).

A non-clustered index on (CustomerID, OrderDate) is a covering index for queries filtering by CustomerID (equality) and OrderDate (range). It allows SQL Server to perform an index seek on CustomerID, then a range scan on OrderDate, retrieving all needed columns without touching the clustered index (if the query is covered). This dramatically reduces logical reads compared to a full clustered index scan or a key lookup.

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 (CustomerID, OrderDate).
Why this is correct
This composite index matches the query pattern exactly: it allows index seek on CustomerID and then range scan on OrderDate, providing optimal performance.
Clue confirmation
The clue word "primary" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
✗
Rebuild the clustered index on (OrderDate, CustomerID).
Why it's wrong here
Changing the clustered index would rearrange the entire table, potentially harming other queries that rely on OrderID ordering. It is a major change with broader impact and may not be the best first approach.
✗
Create a non-clustered index on OrderDate.
Why it's wrong here
This index would require filtering on CustomerID separately, likely leading to many key lookups and still high reads. It is not as efficient as a composite covering index.
✗
Create a filtered index on OrderDate for recent dates.
Why it's wrong here
A filtered index would only benefit queries restricted to the filtered condition (e.g., recent dates) and would not help for historical range queries. It is too narrow in scope.

Common exam traps

Common exam trap: answer the scenario, not the keyword

The trap here is that candidates often think a filtered index or a single-column index is sufficient, but they overlook that the query has both an equality and a range predicate, requiring a composite index that supports both in the correct order (equality first, range second) to achieve optimal seek + range scan performance.

Detailed technical explanation

How to think about this question

Under the hood, a composite non-clustered index stores the key columns in B-tree order, enabling a seek on the leading column (CustomerID) and a range scan on the second column (OrderDate). If the query selects only columns present in the index (or includes them via INCLUDE), SQL Server can satisfy the query entirely from the non-clustered index pages, avoiding costly key lookups into the clustered index. In real-world scenarios, this can reduce logical reads from millions to hundreds for high-volume OLTP 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

Got this wrong? Here's your next step.

Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.

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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 (CustomerID, OrderDate). — A non-clustered index on (CustomerID, OrderDate) is a covering index for queries filtering by CustomerID (equality) and OrderDate (range). It allows SQL Server to perform an index seek on CustomerID, then a range scan on OrderDate, retrieving all needed columns without touching the clustered index (if the query is covered). This dramatically reduces logical reads compared to a full clustered index scan or a key lookup.

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.

Are there clue words in this question I should notice?

Yes — watch for: "primary". Asks for the main purpose or function, not a secondary benefit. Eliminate answers that describe side-effects or partial functions.

What is the key concept behind this question?

Read the scenario before looking for a memorised answer.

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