mediummultiple choiceObjective-mapped

A retail company uses Azure SQL Database for an order management system. The Orders table has columns: OrderID (primary key, clustered), CustomerID, OrderDate, TotalAmount. Queries frequently filter on CustomerID and OrderDate, and sort results by OrderDate in descending order. The queries also return the TotalAmount. Which indexing strategy will most improve query performance for these operations?

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A retail company uses Azure SQL Database for an order management system. The Orders table has columns: OrderID (primary key, clustered), CustomerID, OrderDate, TotalAmount. Queries frequently filter on CustomerID and OrderDate, and sort results by OrderDate in descending order. The queries also return the TotalAmount. Which indexing strategy will most improve query performance for these operations?

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

Maintain the existing clustered index on OrderID only.

Only having a clustered index on OrderID helps queries that filter on OrderID but does not optimize filtering by CustomerID and OrderDate, and sorting by OrderDate will require a full scan.

B

Best answer

Create a nonclustered index on (CustomerID, OrderDate DESC) INCLUDE (TotalAmount).

This index is ordered by CustomerID then OrderDate descending, allowing efficient seeks for a specific CustomerID and range scans over OrderDate in descending order. Including TotalAmount covers the SELECT clause without needing to access the base table.

C

Distractor review

Create a nonclustered index on (OrderDate DESC) INCLUDE (CustomerID, TotalAmount).

OrderDate alone as the leading column cannot efficiently filter by CustomerID; the query would still need to scan all rows for the matching CustomerID within the date range.

D

Distractor review

Create a clustered columnstore index on the entire table.

Clustered columnstore indexes are designed for large data warehousing and analytical queries that aggregate over many rows, not for point lookups or narrow-range queries on transactional tables.

Common exam trap

Common exam trap: NAT rules depend on direction and matching traffic

NAT is not only about the public address. The inside/outside interface roles and the ACL or rule that matches traffic are just as important.

Technical deep dive

How to think about this question

NAT questions usually test address translation, overload/PAT behaviour, static mappings and whether the right traffic is being translated. Read the interface direction and address terms carefully.

KKey Concepts to Remember

  • Static NAT maps one inside address to one outside address.
  • PAT allows many inside hosts to share one public address using ports.
  • Inside local and inside global describe the private and translated addresses.
  • NAT ACLs identify traffic for translation, not always security filtering.

TExam Day Tips

  • Identify inside and outside interfaces first.
  • Check whether the scenario needs static NAT, dynamic NAT or PAT.
  • Do not confuse NAT matching ACLs with normal packet-filtering intent.

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.

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Question 2

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Question 4

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Question 5

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Question 6

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FAQ

Questions learners often ask

What does this DP-900 question test?

Static NAT maps one inside address to one outside address.

What is the correct answer to this question?

The correct answer is: Create a nonclustered index on (CustomerID, OrderDate DESC) INCLUDE (TotalAmount). — A nonclustered index on (CustomerID, OrderDate DESC) that includes TotalAmount as a non-key column (INCLUDE) covers the WHERE clause filter (CustomerID and OrderDate), the ORDER BY (OrderDate DESC is supported because the index is ordered), and includes TotalAmount to avoid a key lookup back to the clustered index. Option A only covers lookups by OrderID, not the filter columns. Option C orders by OrderDate first, but does not include CustomerID as a leading column, so filtering by CustomerID would require scanning many rows. Option D (clustered columnstore) is excellent for large aggregations but not ideal for this transactional query pattern that filters on specific columns and sorts.

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.

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