Question 1hardmultiple choice
Full question →hardmultiple choiceObjective-mapped
An e-commerce application uses Azure SQL Database. The Orders table stores millions of rows with columns: OrderID (primary key, clustered index), CustomerID, OrderDate, OrderStatus, TotalAmount. Queries frequently filter on OrderDate and OrderStatus, and sort results by OrderDate DESC. Which indexing strategy will most improve query performance for these filters and sort?
Answer choices
Why each option matters
Good practice is not just finding the correct option. The wrong answers often show the exact trap the exam wants you to fall into.
A
Distractor review
Create a nonclustered index on OrderDate only.
An index on OrderDate alone would help with filtering by OrderDate and sorting, but it would not help with the additional filter on OrderStatus. The database would still need to filter by OrderStatus after the seek, which may be less efficient.
B
Best answer
Create a nonclustered index on OrderDate, OrderStatus and include other columns needed by the query.
A composite nonclustered index on (OrderDate, OrderStatus) allows the query to filter on both columns efficiently and provides the data already sorted by OrderDate (the leading key). Including other columns avoids key lookups, making the query even faster.
C
Distractor review
Create a clustered columnstore index on the table.
Clustered columnstore indexes are designed for large analytical workloads that scan many rows, not for OLTP queries that filter on specific columns and sort. They may degrade performance for point queries and range scans with sort operations.
D
Distractor review
Create a nonclustered index on OrderStatus only.
An index on OrderStatus alone helps with filtering on OrderStatus, but does not help with the OrderDate filter or sorting by OrderDate. The database would still need to sort the results or scan many rows.
Common exam trap
Common exam trap: answer the scenario, not the keyword
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Technical deep dive
How to think about this question
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
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.
- Use explanations to understand the rule behind the answer.
TExam Day Tips
- Underline the problem statement mentally.
- 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.
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.
More questions from this exam
Keep practising from the same exam bank, or move into a focused topic page if this question exposed a weak area.
Question 1
A data engineer needs to process streaming data from IoT devices and store the results in Azure Data Lake Storage for long-term analytics. The data must be processed in near real-time to detect anomalies and trigger alerts. Which Azure service should the engineer use for stream processing?
Question 2
A data engineer needs to query data stored in CSV files in Azure Data Lake Storage Gen2 using T-SQL in Azure Synapse Analytics, without loading the data into the database. Which feature should they use?
Question 3
A data engineer needs to process raw clickstream data from multiple websites that is stored in Azure Blob Storage as JSON files. The processing must run automatically every hour, transform the data into a structured format for reporting, and handle schema changes in the source data without manual intervention. Which Azure service should be used?
Question 4
A data engineer is designing a data lake architecture in Azure. They plan to first ingest raw data from various sources into a landing zone in Azure Data Lake Storage Gen2. Then they will clean, validate, and deduplicate that data in a second zone. Finally, they will create aggregated, business-ready datasets in a third zone for analysts. This layered approach is known as which architecture?
Question 5
A data engineer needs to transform large datasets stored in Azure Data Lake Storage Gen2 using Python and Apache Spark. They want a serverless compute option that automatically scales and requires no cluster management. Which Azure service should they use?
Question 6
A company collects customer feedback forms. Each form contains always-present fields like CustomerID and SubmissionDate, but also a free-text Comments field and optional fields like Rating or ProductCategory that vary between forms. How should this data be classified?
FAQ
Questions learners often ask
What does this DP-900 question test?
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 OrderDate, OrderStatus and include other columns needed by the query. — Creating a nonclustered index on (OrderDate, OrderStatus) with included columns (if needed) allows the database to perform an index seek for the filter conditions and return rows already sorted by OrderDate. This is more efficient than scanning the clustered index or creating indexes that do not cover the sort order. A columnstore index is optimized for analytical aggregations, not for point lookups or range filters with sorting. An index on OrderOnly does not help with the OrderStatus filter.
What should I do if I get this DP-900 question wrong?
Then try more questions from the same exam bank and focus on understanding why the wrong options are tempting.
Discussion
Loading comments…
Sign in to join the discussion.