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Monitor, configure, and optimize database resourcesmediumMultiple ChoiceObjective-mapped

DP-300 Practice Question: Monitor, configure, and optimize database resources

You manage an Azure SQL Database (General Purpose, S2) used by a reporting application. The database has a table `FactSales` with 500 million rows. Queries that aggregate sales by date are slow. The execution plan shows a clustered index scan on `FactSales`. The table has a clustered index on `SaleID` and a nonclustered index on `DateKey`. The queries filter by `DateKey` and `ProductKey`. You need to improve query performance without changing the service tier. Which action should you take?

⚠ Common exam trap

Many candidates choose partitioning (Option B) thinking it speeds up all queries by date, but without a covering index, partitioning alone does not eliminate the scan; it only reduces the data scanned to a single partition.

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 covering index on DateKey and ProductKey including the aggregated columns.

The query filters by DateKey and ProductKey and aggregates sales data. A covering index on DateKey and ProductKey that includes the aggregated columns (e.g., SUM(SalesAmount)) allows the query to be satisfied entirely from the index without touching the clustered index, eliminating the costly clustered index scan. This is the most direct and effective way to improve performance without changing the service tier.

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 ProductKey only.

    Why it's wrong here

    ProductKey index alone does not cover the query.

  • Partition the table by DateKey.

    Why it's wrong here

    Partitioning does not guarantee index seeks.

  • Create a clustered columnstore index on the table.

    Why it's wrong here

    Columnstore is for DW, not OLTP.

  • Create a covering index on DateKey and ProductKey including the aggregated columns.

    Why this is correct

    Covering index provides index seeks and avoids lookups.

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Written by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

This DP-300 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-300 exam.