DP-900 Practice Test 17 — 15 Questions

Question 1

A banking application processes fund transfers. When a transfer is executed, the system must either successfully debit one account and credit the other, or if any step fails, the entire operation must be rolled back so no partial changes remain. Which ACID property directly enforces this behavior?

Accepted Answer

A) Atomicity. Atomicity ensures that a transaction is treated as a single, indivisible unit of work. In this banking scenario, the debit and credit operations are part of one transaction; if either step fails, the entire transaction is rolled back, leaving no partial changes. This is the core property that enforces the 'all-or-nothing' behavior described.

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B) Consistency

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C) Isolation

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D) Durability

Question 2

A business analyst needs to query a large Azure SQL Database table that stores sales transactions. The table contains over 100 million rows. The analyst wants to retrieve aggregated sales per product category for the current month. The current query performs a full table scan and takes several minutes. Which indexing strategy will best improve the performance of this aggregation query?

Accepted Answer

Create a columnstore index on the table. A columnstore index stores data column-wise and uses batch processing, which dramatically accelerates aggregation queries (like SUM, COUNT, GROUP BY) over large tables. For a 100-million-row table, this reduces I/O and CPU by reading only the columns needed for the aggregation, making it the optimal choice for the analyst's current-month sales-per-category query.

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Create a clustered index on the transaction date column

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Create a nonclustered index on the product category column

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Create a filtered index on transactions from the current month

Question 3

A company has a table named 'Sales' in Azure SQL Database with columns: SaleID (int, primary key), ProductID (int), SaleDate (datetime), Quantity (int), UnitPrice (decimal), TotalAmount (computed column). Queries frequently run to retrieve the total Quantity and UnitPrice for a specific ProductID over a date range. The query filters on ProductID and SaleDate and selects only Quantity and UnitPrice. Which index would most improve query performance?

Accepted Answer

Nonclustered index on (ProductID, SaleDate) INCLUDE (Quantity, UnitPrice). Option A is correct because it creates a covering nonclustered index that supports both the WHERE clause (ProductID, SaleDate) and the SELECT clause (Quantity, UnitPrice) without needing to access the base table. The index key order matches the query filter, and the included columns avoid key lookups, minimizing I/O for the frequent aggregation queries.

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Nonclustered index on (SaleDate) INCLUDE (Quantity, UnitPrice)

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Clustered index on (ProductID, SaleDate)

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Nonclustered index on (ProductID) INCLUDE (Quantity, UnitPrice)

Question 4

A company is evaluating Azure database services for two different workloads. Workload A processes high-volume, low-latency transactions such as order entry and payment processing, where each transaction updates a few rows. Workload B involves running complex aggregations on terabytes of historical sales data to generate monthly business intelligence reports. Which Azure service is best suited for each workload?

Accepted Answer

B. Workload A: Azure Cosmos DB; Workload B: Azure Synapse Analytics. Workload A requires a low-latency, high-throughput transactional database capable of handling many small, row-level updates. Azure Cosmos DB is a NoSQL database designed for single-digit millisecond latency and horizontal scaling, making it ideal for order entry and payment processing. Workload B involves complex aggregations on terabytes of historical data, which is best handled by Azure Synapse Analytics, a distributed analytics service that uses massively parallel processing (MPP) to run large-scale queries efficiently.

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A. Workload A: Azure SQL Database; Workload B: Azure Cosmos DB

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C. Workload A: Azure Synapse Analytics; Workload B: Azure SQL Database

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D. Workload A: Azure Cosmos DB; Workload B: Azure Cosmos DB

Question 5

A company stores backup files in Azure Blob Storage. The backup files are accessed frequently for the first 30 days, then only rarely for the next six months. After one year, the files must be retained for compliance but are never accessed. The company wants to minimize storage costs. Which solution should they use?

Accepted Answer

Use Azure Blob Storage lifecycle management policies. Azure Blob Storage lifecycle management policies allow you to automatically transition blobs to cooler tiers (e.g., from Hot to Cool after 30 days, then to Archive after one year) and delete blobs after a specified period, all without manual intervention. This directly matches the access pattern: frequent access for 30 days, rare access for six months, and never accessed after one year, minimizing storage costs by using the most cost-effective tier for each phase.

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Manually move files between storage accounts

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Use Azure File Sync

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Use Azure NetApp Files

Question 6

A company has an existing IoT application that uses Apache Cassandra for time-series sensor data. They want to migrate to Azure's fully managed NoSQL database service while continuing to use the Cassandra Query Language (CQL) and benefiting from global distribution and low latency. Which Azure Cosmos DB API should they use?

Accepted Answer

Cassandra API. The Cassandra API for Azure Cosmos DB is wire-protocol-compatible with Apache Cassandra, meaning you can use existing CQL (Cassandra Query Language) tools, drivers, and code with minimal changes. It provides a fully managed, globally distributed NoSQL database with low-latency reads and writes, which directly matches the company's requirement to migrate from self-managed Cassandra while preserving their CQL-based application logic.

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Core (SQL) API

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MongoDB API

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Gremlin API

Question 7

A company runs an e-commerce application on Azure SQL Database. During seasonal promotions, traffic spikes significantly, but at other times traffic is low. They want to automatically adjust compute resources based on demand without manual intervention or provisioning. Which Azure SQL Database feature should they use?

Accepted Answer

Serverless compute. Serverless compute for Azure SQL Database automatically scales compute resources based on workload demand and pauses the database during inactive periods, charging only for storage and compute used per second. This matches the requirement for automatic adjustment without manual intervention or provisioning, especially for intermittent, unpredictable traffic spikes like seasonal promotions.

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Geo-replication

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Elastic pools

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Hyperscale

Question 8

A company runs a critical OLTP application on a single Azure SQL Database in the West US region. They need to ensure high availability with automatic failover to a secondary region in case of a regional outage. The solution must minimize data loss and allow the secondary database to be readable for reporting queries when the primary is healthy. Which feature should they enable?

Accepted Answer

Failover groups with automatic failover policy. Failover groups with an automatic failover policy enable Azure SQL Database to replicate data synchronously to a secondary region, ensuring zero data loss during a planned failover and minimal data loss during an unplanned failover. The secondary database is readable for reporting queries when the primary is healthy, meeting both the high availability and read-scale requirements. This feature is specifically designed for cross-region disaster recovery with automatic failover, unlike other options that address security, backup retention, or performance tuning.

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Transparent Data Encryption (TDE)

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Long-term backup retention (LTR)

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Auto-tuning

Question 9

A company maintains a large 'Transactions' table in Azure SQL Database. The table has a clustered index on a GUID column (TransactionID). Over time, they observe slow insert performance due to index fragmentation and page splits. They also need fast point lookups by TransactionID. Which approach should they take to improve insert performance while still supporting fast lookups?

Accepted Answer

Change the clustered key to an integer IDENTITY column and keep a nonclustered index on TransactionID. Option B is correct because using an integer IDENTITY column as the clustered key eliminates the random insertion order and page splits caused by a GUID clustered index, while the nonclustered index on TransactionID provides fast point lookups. In Azure SQL Database, a clustered index determines the physical order of data; a monotonically increasing integer avoids fragmentation and improves insert throughput.

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Change the clustered index to a nonclustered index on TransactionID and make the table a heap

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Keep the clustered index on TransactionID but rebuild it daily

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Remove the clustered index entirely and create a nonclustered index on TransactionID

Question 10

A company runs a global e-commerce application on Azure SQL Database. The application has a read-intensive workload with millions of users querying product details simultaneously. The database is experiencing high read latency during peak hours due to the volume of concurrent read requests. The company wants to scale read performance without changing the application code and without affecting write operations. Which Azure SQL Database feature should they implement?

Accepted Answer

Active geo-replication. Active geo-replication creates readable secondary replicas of the Azure SQL Database in different Azure regions. By configuring read-only routing to these secondaries, the application can offload read queries from the primary database, scaling read performance without any code changes and without impacting write operations on the primary.

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Elastic pools

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In-memory OLTP

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Columnstore indexes

Question 11

A company needs to migrate 10 on-premises SQL Server databases (each 50–200 GB) to Azure. The databases frequently run cross-database queries using three-part names (e.g., DB1.dbo.table) and rely on SQL Server Agent for maintenance tasks. They want to minimize management overhead and share resources across databases to reduce costs. Which Azure SQL deployment option should they choose?

Accepted Answer

Azure SQL Managed Instance. Azure SQL Managed Instance is correct because it provides native support for cross-database queries using three-part names (e.g., DB1.dbo.table) and SQL Server Agent for maintenance tasks, which are critical requirements. It also offers a fully managed platform that minimizes management overhead while allowing resource sharing across databases within the instance, reducing costs compared to single databases or VMs.

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Azure SQL Database elastic pool

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SQL Server on Azure Virtual Machine

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Azure SQL Database single database

Question 12

A company runs a customer-facing application on an Azure SQL Database. The application experiences high read traffic from reporting queries that cause performance degradation on the primary database. The company needs a solution that offloads reporting queries without impacting the transactional workload, and the solution must keep the reporting data synchronized within seconds. Which feature should they use?

Accepted Answer

Active Geo-Replication. Active Geo-Replication creates a readable secondary replica of the Azure SQL Database in a different Azure region. This secondary replica can handle read-only reporting queries, offloading them from the primary database, and data is synchronized asynchronously with a typical lag of seconds, meeting the near-real-time synchronization requirement without impacting the transactional workload.

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Auto-failover groups

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Elastic Database Transactions

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Database Copy

Question 13

A company uses Azure SQL Database for an e-commerce application. The Orders table contains columns: OrderID (int, primary key), CustomerID (int), OrderDate (datetime), TotalAmount (decimal). Queries frequently filter by both CustomerID and OrderDate to retrieve orders for a specific customer within a date range. Which indexing strategy will most improve the performance of these queries?

Accepted Answer

Create a nonclustered index on (CustomerID, OrderDate).. Option B is correct because a nonclustered index on (CustomerID, OrderDate) directly supports the query filter that uses both columns. The index is ordered by CustomerID first, enabling SQL Server to quickly locate all rows for a specific customer, and then within that customer, the OrderDate column is ordered to efficiently scan the date range. This index covers the query's WHERE clause without needing to scan the entire table.

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Create a clustered index on OrderID.

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Create a nonclustered index on (OrderDate, CustomerID).

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Create a nonclustered index on TotalAmount.

Question 14

A company runs a web application on Azure SQL Database that experiences unpredictable spikes in traffic. They want to automatically adjust compute resources based on demand without manual intervention and without over-provisioning. Which Azure SQL Database feature should they use?

Accepted Answer

Serverless compute tier. The Serverless compute tier for Azure SQL Database automatically scales compute resources based on workload demand, pausing databases during idle periods and resuming them when traffic spikes occur. This eliminates the need for manual intervention and prevents over-provisioning by charging only for the compute used per second, making it ideal for unpredictable traffic patterns.

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Active geo-replication

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Hyperscale service tier

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Read scale-out

Question 15

A company stores user profile images in Azure Blob Storage. Each image is accessed via a URL that includes a Shared Access Signature (SAS) token generated using the storage account key. The company needs to immediately revoke access to all images for a specific user. Which action should they take?

Accepted Answer

Change the storage account access keys.. Option B is correct because changing the storage account access keys invalidates all SAS tokens that were generated using those keys, including any existing tokens. This immediately revokes access to all images for all users, including the specific user, without needing to manage individual tokens. SAS tokens are signed with the account key, so rotating the key renders all tokens generated with the old key invalid.

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Delete the individual SAS tokens associated with that user's images.

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Delete the container containing the user's images.

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Regenerate the SAS token for each image.