- A
Create a nonclustered index on CustomerID and ShipDate
This composite index covers both filter columns, enabling efficient seek operations for the WHERE clause conditions.
- B
Create a clustered index on ShipmentID
Why wrong: A clustered index on the primary key helps for lookups by ShipmentID but does not improve filtering on CustomerID and ShipDate; the query would still require a full scan or separate index.
- C
Partition the table by ShipmentID
Why wrong: Partitioning by ShipmentID does not align with the common query filters (CustomerID, ShipDate). Partition elimination would not occur, so performance gains are minimal.
- D
Create a full-text index on Destination
Why wrong: Full-text indexes are designed for searching words or phrases in text columns, not for range or equality queries on CustomerID and ShipDate.
Quick Answer
The correct choice is to create a nonclustered index on CustomerID and ShipDate. This composite index directly supports the frequent query pattern of filtering by both columns, enabling the Azure SQL Database engine to perform an index seek rather than a full table scan, which drastically reduces I/O and speeds up retrieval across millions of rows. On the Microsoft Azure Data Fundamentals DP-900 exam, this scenario tests your understanding of indexing strategies for multi-column filters, often appearing as a question where a single-column index on CustomerID alone is a tempting but incomplete answer—it would still require a key lookup for each date range. A common trap is assuming any index on both columns works regardless of column order; remember that the leftmost column in the index definition must match the filter’s most selective column for optimal seek performance. Memory tip: think of a phone book sorted by last name then first name—you can’t efficiently look up all “Johns” without a last name, just as an index on (ShipDate, CustomerID) won’t help if you filter by CustomerID first.
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 logistics company uses Azure SQL Database to store millions of shipment records. The table has columns: ShipmentID (primary key), CustomerID, ShipDate, and Destination. Queries frequently filter by CustomerID and ShipDate to retrieve shipments for a specific customer over a date range. Which indexing strategy will most improve query performance?
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.
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 nonclustered index on CustomerID and ShipDate
A nonclustered index on CustomerID and ShipDate is the best choice because it directly supports the frequent query pattern filtering by both columns. This composite index allows SQL Database to perform an index seek rather than a full table scan, drastically reducing I/O for selective queries over millions of rows.
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 nonclustered index on CustomerID and ShipDate
Why this is correct
This composite index covers both filter columns, enabling efficient seek operations for the WHERE clause conditions.
Clue confirmation
The clue word "primary" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Create a clustered index on ShipmentID
Why it's wrong here
A clustered index on the primary key helps for lookups by ShipmentID but does not improve filtering on CustomerID and ShipDate; the query would still require a full scan or separate index.
- ✗
Partition the table by ShipmentID
Why it's wrong here
Partitioning by ShipmentID does not align with the common query filters (CustomerID, ShipDate). Partition elimination would not occur, so performance gains are minimal.
- ✗
Create a full-text index on Destination
Why it's wrong here
Full-text indexes are designed for searching words or phrases in text columns, not for range or equality queries on CustomerID and ShipDate.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often assume a clustered index on the primary key is always optimal, but for queries that filter on non-key columns, a covering nonclustered index is far more effective.
Trap categories for this question
Keyword trap
Full-text indexes are designed for searching words or phrases in text columns, not for range or equality queries on CustomerID and ShipDate.
Detailed technical explanation
How to think about this question
Under the hood, SQL Server uses a B-tree structure for nonclustered indexes. When the index includes both CustomerID and ShipDate as key columns, the query optimizer can perform an index seek to locate the exact rows matching the customer and date range, then optionally use included columns to cover the query without touching the clustered index. In a real-world scenario with millions of rows, this can reduce query time from seconds to milliseconds, especially when the date range is narrow.
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.
- →
Identify considerations for relational data on Azure — study guide chapter
Learn the concepts, then practise the questions
- →
Identify considerations for relational data on Azure practice questions
Targeted practice on this topic area only
- →
All DP-900 questions
982 questions across all exam domains
- →
Microsoft Azure Data Fundamentals DP-900 study guide
Full concept coverage aligned to exam objectives
- →
DP-900 practice test guide
How to use practice tests most effectively before exam day
Related practice questions
Related DP-900 practice-question pages
Use these pages to review the topic behind this question. This is how one missed question becomes focused revision.
Describe core data concepts practice questions
Practise DP-900 questions linked to Describe core data concepts.
Describe an analytics workload on Azure practice questions
Practise DP-900 questions linked to Describe an analytics workload on Azure.
Identify considerations for relational data on Azure practice questions
Practise DP-900 questions linked to Identify considerations for relational data on Azure.
Describe considerations for working with non-relational data on Azure practice questions
Practise DP-900 questions linked to Describe considerations for working with non-relational data on Azure.
DP-900 fundamentals practice questions
Practise DP-900 questions linked to DP-900 fundamentals.
DP-900 scenario practice questions
Practise DP-900 questions linked to DP-900 scenario.
DP-900 troubleshooting practice questions
Practise DP-900 questions linked to DP-900 troubleshooting.
Practice this exam
Start a free DP-900 practice session
Short sessions build daily habit. Longer sessions build exam-day stamina. Try a timed session to simulate real conditions.
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 nonclustered index on CustomerID and ShipDate — A nonclustered index on CustomerID and ShipDate is the best choice because it directly supports the frequent query pattern filtering by both columns. This composite index allows SQL Database to perform an index seek rather than a full table scan, drastically reducing I/O for selective queries over millions of rows.
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.
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 →
Same concept, more angles
1 more ways this is tested on DP-900
These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. 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?
medium- ✓ A.Create a non-clustered index on OrderDate and CustomerID
- B.Create a clustered index on OrderDate
- C.Create a non-clustered index on OrderID
- D.Partition the table by CustomerID
Why A: 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.
Last reviewed: Jun 11, 2026
This DP-900 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-900 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.