The answer is to update statistics and create a covering nonclustered index on the columns used in the query. A clustered index scan occurs when the query optimizer lacks precise data distribution information or a suitable index to satisfy the query without scanning every row; updating statistics refreshes this metadata, often enabling a more efficient seek or range scan, while a covering nonclustered index eliminates the need to access the clustered index entirely by including all referenced columns. On the Microsoft Azure Database Administrator Associate DP-300 exam, this scenario tests your ability to interpret Query Performance Insight and plan cache data, with a common trap being to immediately add indexes without first checking for stale statistics—a low-cost, non-disruptive step that can resolve many performance issues. Remember the mnemonic "Stats First, Index Last" to avoid unnecessary schema changes when optimizing a query with a clustered index scan in Azure SQL Database.
DP-300 Practice Question: Monitor, configure, and optimize database resources
This DP-300 practice question tests your understanding of monitor, configure, and optimize database resources. 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.
You are monitoring an Azure SQL Database using Query Performance Insight and notice that a specific query has a high average duration and high CPU usage. The query plan shows a clustered index scan on a large table. Which two actions should you take to optimize performance? (Choose two.)
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Update statistics on the table to ensure the optimizer has current information.
Option B is correct because updating statistics provides the query optimizer with current data distribution information, which can lead to a more efficient query plan, potentially avoiding the clustered index scan. In Azure SQL Database, stale statistics are a common cause of suboptimal plans, and updating them is a low-cost, non-disruptive first step before considering index changes.
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.
✗
Rebuild the clustered index to reduce fragmentation.
Why it's wrong here
Fragmentation is not the primary issue; a scan is due to missing indexes.
✓
Update statistics on the table to ensure the optimizer has current information.
Why this is correct
Up-to-date statistics help the optimizer choose efficient plans.
Related concept
Read the scenario before looking for a memorised answer.
✗
Force a different query plan using Query Store hints.
Why it's wrong here
Forcing a plan without analysis can cause performance regression.
✗
Increase the DTU service tier of the database.
Why it's wrong here
DTU model is not applicable to vCore-based Azure SQL Database.
✓
Create a covering nonclustered index on the columns used in the query.
Why this is correct
A covering index can replace the scan with a seek.
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 jump to index rebuilds or scaling up resources, overlooking that stale statistics are a frequent and easily fixable cause of poor query plans in Azure SQL Database.
Detailed technical explanation
How to think about this question
When a query performs a clustered index scan, it reads all rows in the table; updating statistics can change the estimated row count and cardinality, potentially enabling the optimizer to choose a seek operation or a different join strategy. In Azure SQL Database, automatic statistics updates occur by default but may not trigger for large tables with frequent modifications, so manual updates are sometimes necessary. A covering nonclustered index (option E) can eliminate the scan entirely by including all columns referenced in the query, allowing index-only access without touching the clustered index.
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 startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.
Related glossary terms
Concepts from this question explained
These glossary pages explain the core terms tested in this DP-300 question in full detail.
Monitor, configure, and optimize database resources — This question tests Monitor, configure, and optimize database resources — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Update statistics on the table to ensure the optimizer has current information. — Option B is correct because updating statistics provides the query optimizer with current data distribution information, which can lead to a more efficient query plan, potentially avoiding the clustered index scan. In Azure SQL Database, stale statistics are a common cause of suboptimal plans, and updating them is a low-cost, non-disruptive first step before considering index changes.
What should I do if I get this DP-300 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.
About these practice questions
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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. You are monitoring an Azure SQL Database using Query Performance Insight. You see a query with high duration and high CPU usage. The query plan shows a clustered index scan. What is the most likely cause and recommendation?
medium
A.Fragmented clustered index; rebuild the clustered index.
B.Insufficient memory; increase the service tier.
✓ C.Missing nonclustered index; create an index on the predicates.
D.Parameter sniffing; add OPTION (RECOMPILE).
Why C: Query Performance Insight shows a query with high duration and CPU usage, and the query plan reveals a clustered index scan. A clustered index scan reads all rows in the table, which is inefficient when only a subset of rows is needed. The most likely cause is a missing nonclustered index on the columns used in the WHERE clause (predicates), which would allow a seek operation instead of a full scan, reducing both CPU and duration.
Last reviewed: Jun 11, 2026
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