DP-900 Practice Test 5 — 10 Questions

Question 1

A company uses Azure SQL Database for an inventory management system. The Inventory table has millions of rows. Queries frequently filter on WarehouseID and then sort by LastUpdatedDate. The table currently has a clustered index on InventoryID (primary key). Which action will most improve query performance for these frequent filters?

Accepted Answer

Create a non-clustered index on (WarehouseID, LastUpdatedDate) INCLUDE (Quantity). A non-clustered index on (WarehouseID, LastUpdatedDate) allows the database engine to efficiently locate rows matching a specific WarehouseID and return them already sorted by LastUpdatedDate without accessing the clustered index (or with minimal lookup). Including the Quantity column as a non-key included column avoids key lookups for that column, further improving performance. Changing the clustered index to WarehouseID could cause fragmentation and is not ideal for uniqueness. A single-column index on LastUpdatedDate does not support the filter on WarehouseID. Partitioning by InventoryID does not help this query pattern.

Answer

Add a clustered index on WarehouseID

Answer

Create a non-clustered index on LastUpdatedDate only

Answer

Partition the table by InventoryID

Question 2

A company uses Azure SQL Database for its e-commerce platform. The reporting team runs complex, long-running queries that join multiple tables and would degrade performance of the transactional workload if executed on the primary database. Which Azure SQL Database feature should the company enable to isolate the reporting queries while ensuring read-only access to the most current data?

Accepted Answer

Read scale-out (read-only replicas). Read scale-out (read-only replicas) allows you to offload reporting queries to a read-only replica of the Azure SQL Database, ensuring that complex, long-running queries do not degrade the performance of the primary transactional workload. The replica provides access to the most current data because it uses snapshot isolation and is transactionally consistent with the primary database.

Answer

Automatic tuning

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Geo-replication

Answer

Elastic query

Question 3

A company uses Azure SQL Database for an e-commerce application. The Orders table has millions of rows. Queries that filter on CustomerID and order by OrderDate are slow. The table currently has a clustered index on OrderID (the primary key). Which index strategy will best improve these queries?

Accepted Answer

C. Create a nonclustered index on (CustomerID, OrderDate).. Option C is correct because creating a nonclustered index on (CustomerID, OrderDate) directly supports the query's filter (WHERE CustomerID = ?) and sort (ORDER BY OrderDate) operations. This composite index allows SQL Server to seek on CustomerID and then retrieve rows in OrderDate order without a separate sort, eliminating the need for a full clustered index scan on OrderID. It is a covering index for this query pattern, significantly reducing I/O and CPU overhead.

Answer

A. Create a nonclustered index on OrderDate only.

Answer

B. Create a filtered index on CustomerID where Status = 'Active'.

Answer

D. Create a nonclustered index on OrderID and OrderDate.

Question 4

A company uses Azure SQL Database to store customer order data. They need to automatically track changes to the 'OrderStatus' column in the 'Orders' table. They want to be able to query the current status and also easily retrieve historical status changes for a given order without writing custom triggers or history tables. Which feature should they enable?

Accepted Answer

Temporal tables. Temporal tables (system-versioned) automatically track full row history, including changes to the 'OrderStatus' column, by maintaining a paired history table. This allows querying both current and historical states with simple T-SQL clauses like FOR SYSTEM_TIME, without custom triggers or manual history tables.

Answer

Change Data Capture (CDC)

Answer

Automatic tuning

Answer

Geo-replication

Question 5

A company stores an employee database in a relational database. The Employees table includes columns: EmployeeID (integer), FirstName (text), LastName (text), HireDate (date), and a column called Photo which stores the employee's photo as a binary large object (BLOB). Which statement best describes the data types in this table?

Accepted Answer

The Photo column stores unstructured data, while the other columns store structured data.. The Photo column stores a binary large object (BLOB), which is unstructured data because it does not have a predefined schema or format that can be easily queried or indexed by relational operations. In contrast, EmployeeID, FirstName, LastName, and HireDate are all structured data types (integer, text, date) that conform to a fixed schema and support direct querying, sorting, and indexing. This distinction is fundamental in Azure data services, where structured data is typically stored in Azure SQL Database or Azure Synapse, while unstructured BLOBs are better suited for Azure Blob Storage.

Answer

All columns store structured data.

Answer

All columns store unstructured data.

Answer

The HireDate column stores semi-structured data.

Question 6

A company wants to build a modern data warehouse using a lakehouse architecture. They need to store raw data in its native format (e.g., CSV, JSON, Parquet) and also support BI reporting on curated, transformed data. They want to use a single storage layer for both raw and curated data. Which Azure service should they use as the core storage layer?

Accepted Answer

Azure Data Lake Storage Gen2. Azure Data Lake Storage Gen2 (ADLS Gen2) is the correct choice because it provides a single, unified storage layer that can store raw data in its native format (CSV, JSON, Parquet) in a hierarchical namespace, while also serving as the foundation for curated, transformed data used in BI reporting. It combines the scalability and cost-effectiveness of Azure Blob Storage with the file system semantics and ACLs needed for analytics workloads, making it the ideal core storage layer for a lakehouse architecture.

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Azure SQL Database

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Azure Synapse Analytics

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Azure Cosmos DB

Question 7

A development team is designing a relational database for a hospital patient management system. They need to ensure that each patient's medical record number is unique and not null. Which database constraint should they use?

Accepted Answer

PRIMARY KEY. The PRIMARY KEY constraint enforces both uniqueness and non-nullability on the column(s) it is applied to. In a relational database, the medical record number is the natural candidate for the primary key of the Patient table because it uniquely identifies each patient and must always have a value. This directly meets the requirement that each patient's medical record number is unique and not null.

Answer

FOREIGN KEY

Answer

CHECK

Answer

UNIQUE

Question 8

A company uses Azure SQL Database for an HR system. The Employees table has a clustered index on EmployeeID. Queries frequently filter on DepartmentID and LastName and also retrieve the Salary column. The table contains over a million rows. Which index strategy will most improve query performance for these filters?

Accepted Answer

A: Create a nonclustered index on (DepartmentID, LastName) INCLUDE (Salary). Option A is correct because it creates a covering nonclustered index on the filter columns (DepartmentID, LastName) and includes the Salary column as an included column. This allows the query to be fully satisfied by scanning only the nonclustered index pages, avoiding key lookups to the clustered index. The order of columns in the index key matches the query filter pattern, maximizing seek efficiency.

Answer

B: Create a nonclustered index on LastName only

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C: Create a nonclustered index on DepartmentID and another nonclustered index on LastName

Answer

D: Change the clustered index to (DepartmentID, LastName)

Question 9

A company uses Azure Synapse Analytics dedicated SQL pool as its data warehouse. New data is loaded into the warehouse every few minutes. The company wants to visualize the data with near real-time updates in a dashboard that can be refreshed automatically. Which tool and connection mode should they use?

Accepted Answer

Power BI with DirectQuery mode. Power BI with DirectQuery mode is correct because it allows the dashboard to query the Azure Synapse dedicated SQL pool directly for each visual refresh, enabling near real-time updates without importing data. This mode avoids the latency of data import and supports automatic page refresh, which aligns with the requirement for data loaded every few minutes.

Answer

Azure Data Studio with visualizations

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SQL Server Reporting Services (SSRS) with cached reports

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Excel Power Pivot with imported data

Question 10

A database administrator manages an Azure SQL Database with a table that has a clustered index on OrderID. Frequent queries filter on OrderDate and then sort the results by CustomerID. These queries perform poorly. Which indexing strategy will most improve performance for these specific queries?

Accepted Answer

Create a nonclustered index on (OrderDate, CustomerID). The query filters on OrderDate and then sorts by CustomerID. A nonclustered index on (OrderDate, CustomerID) supports both the WHERE clause (by OrderDate) and the ORDER BY clause (by CustomerID) as a covering index, allowing the database engine to perform a single index seek or scan without needing a separate sort operation. This directly addresses the performance bottleneck by eliminating the need to sort the results after filtering.

Answer

Create a nonclustered index on (CustomerID, OrderDate)

Answer

Change the clustered index to (OrderDate)

Answer

Create a filtered index on OrderDate WHERE CustomerID IS NOT NULL