DP-900 Practice Test 14 — 15 Questions

Question 1

Refer to the exhibit. You are reviewing an ARM template for an Azure SQL Database deployment. The database must support a read-only workload that requires low latency. The current configuration uses General Purpose tier with 4 vCores. What is the most significant performance improvement you can make without changing the tier?

Choose an answer to begin — your selection is scored in the full session.

Accepted Answer

Enable read scale-out by adding 'readScale' property. Enabling read scale-out by adding the 'readScale' property allows the database to use a read-only replica, offloading read workloads from the primary and providing low-latency reads. This is the most significant performance improvement within the General Purpose tier because it directly addresses the read-only workload requirement without changing the tier or incurring additional compute costs.

Answer

Increase maxSizeBytes to 1 TB

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Set the edition to 'Serverless'

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Change requestedBackupStorageRedundancy to 'Local'

Question 2

A company needs to analyze streaming data from IoT devices in real time. They want to identify anomalies and trigger alerts. Which Azure service should they use as the core processing engine?

Accepted Answer

Azure Stream Analytics. Azure Stream Analytics is purpose-built for real-time stream processing, allowing you to define SQL-like queries that run continuously against streaming data from sources like IoT Hub. It can detect anomalies and trigger alerts on the fly, making it the correct core processing engine for this IoT scenario.

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Azure Synapse Analytics

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Azure Databricks

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Azure Data Lake Storage

Question 3

You are a data architect for a healthcare organization. The organization needs to build a real-time analytics solution to monitor patient vital signs from IoT devices. The data arrives at a rate of 10,000 events per second. Each event contains patient ID, timestamp, heart rate, blood pressure, and oxygen saturation. The solution must alert clinicians within 10 seconds when a patient's vital signs exceed predefined thresholds. Additionally, the solution must store the raw data for historical analysis and compliance. You plan to use Azure Event Hubs for ingestion. Which combination of services should you use to meet the requirements? Consider: processing low latency alerts, storing raw data in cost-effective storage, and enabling historical analytics. You also need to ensure that the solution can scale to handle future growth.

Accepted Answer

Use Azure Stream Analytics for real-time processing and alerting, output data to Azure Data Lake Storage, and use Azure Synapse Serverless SQL for historical analytics. Azure Stream Analytics provides low-latency (sub-second) stream processing and can trigger alerts within the 10-second requirement. Outputting raw data to Azure Data Lake Storage (ADLS) offers cost-effective storage for compliance, and Azure Synapse Serverless SQL enables on-demand historical analytics without provisioning dedicated compute, scaling automatically for future growth.

Answer

Use Azure Databricks with Structured Streaming, store data in Delta Lake, and use Power BI for real-time dashboards

Answer

Use Azure Data Factory to batch ingest events every minute, store in Azure Blob Storage, and use Azure Analysis Services for historical analytics

Answer

Use Azure Functions to process events, store data in Azure Cosmos DB, and use Power BI for historical analytics

Question 4

Your company has a Power BI dashboard that uses a data model with a single large fact table and several dimension tables. The dashboard loads slowly when users filter by multiple dimensions. Which design change would MOST improve performance?

Accepted Answer

Ensure the fact table and dimension tables follow a star schema design with proper relationships.. A star schema design with proper relationships between the fact table and dimension tables is the foundational best practice for optimizing Power BI data models. This design minimizes the cardinality of relationships, reduces the size of the data model, and enables efficient query folding and storage engine compression, which directly improves filter performance across multiple dimensions.

Answer

Use page-level filters instead of report-level filters.

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Create a calculated table that aggregates the fact table at a higher granularity.

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Convert the data model to a composite model using DirectQuery for some tables.

Question 5

Your company stores customer data in Azure Blob Storage. To comply with data residency regulations, you must ensure data is replicated within the same Azure region. Which replication option should you choose?

Accepted Answer

Locally-redundant storage (LRS). Locally-redundant storage (LRS) replicates data three times within a single physical location in the same Azure region, ensuring data residency compliance by never copying data outside that region. This is the only option that guarantees all replicas stay within one region without any cross-region or cross-zone replication.

Answer

Zone-redundant storage (ZRS)

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Geo-redundant storage (GRS)

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Read-access geo-redundant storage (RA-GRS)

Question 6

You are implementing a data pipeline that ingests millions of events per second from IoT devices. The pipeline must tolerate failures and guarantee exactly-once processing. Which Azure service should you use to ingest the events?

Accepted Answer

Azure Event Hubs. Azure Event Hubs is the correct choice because it is a big data streaming platform and event ingestion service designed for high-throughput scenarios, capable of ingesting millions of events per second. It supports exactly-once processing through checkpointing and partition-based offset management, and its built-in replication and availability zones provide fault tolerance.

Answer

Azure IoT Hub

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Azure Service Bus

Answer

Azure Queue Storage

Question 7

Refer to the exhibit. You are analyzing a message from an IoT device captured in Azure Event Hubs. The message contains system properties indicating the device ID and authentication method. You need to route messages from device-01 to a separate storage container for compliance. Which property should you use in a Stream Analytics query to filter messages?

Accepted Answer

iothub-connection-device-id. The `iothub-connection-device-id` system property is automatically added by Azure IoT Hub to every device-to-cloud message. In a Stream Analytics query, you can reference this property directly (e.g., `WHERE iothub-connection-device-id = 'device-01'`) to filter messages from a specific device for routing to a separate storage container for compliance.

Answer

partitionId

Answer

consumerGroup

Answer

deviceId

Question 8

A company wants to store historical sales data for long-term analysis. The data is accessed infrequently but must be retained for 7 years. Which Azure storage tier minimizes cost while meeting these requirements?

Accepted Answer

Cool storage tier. The Cool storage tier is designed for data that is accessed infrequently but must be retained for extended periods, offering lower storage costs than Hot tier while still providing low-latency access when needed. With a 30-day minimum storage duration and a cost structure optimized for infrequent reads, it balances cost and accessibility for 7-year retention of historical sales data.

Answer

Archive storage tier

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Premium storage tier

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Hot storage tier

Question 9

A company ingests streaming data from thousands of devices into Azure Event Hubs. They need to transform and aggregate the data in real time before storing it in Azure Data Lake Storage Gen2. Which Azure service should they use between Event Hubs and ADLS Gen2?

Accepted Answer

Azure Stream Analytics. Azure Stream Analytics is purpose-built for real-time data processing and analytics, allowing you to define SQL-like queries to transform and aggregate streaming data from Event Hubs before outputting it directly to Azure Data Lake Storage Gen2. It provides exactly-once delivery semantics and low-latency processing, making it the ideal service for this ingestion-to-storage pipeline.

Answer

Azure Functions

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Azure Databricks

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Azure Data Factory

Question 10

A financial database system ensures that once a transaction is committed, the data changes are permanently stored and will survive any subsequent system failure, such as a power outage or crash. Which property of ACID transactions does this describe?

Accepted Answer

D: Durability. D is correct because durability guarantees that once a transaction is committed, the changes persist permanently, even in the event of a system failure like a power outage or crash. In SQL Server, this is implemented via the write-ahead log (WAL) and checkpoint processes, ensuring committed data is flushed to disk before acknowledging success.

Answer

A: Atomicity

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B: Consistency

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C: Isolation

Question 11

A retail company collects streaming clickstream data from its website into Azure Event Hubs. They need to aggregate the data in real-time to count page views per product every minute and store the results in Azure SQL Database for a live dashboard. Which Azure service should they use to perform this real-time aggregation?

Accepted Answer

Azure Stream Analytics. Azure Stream Analytics is purpose-built for real-time stream processing, allowing you to define a query that aggregates clickstream data from Event Hubs using a tumbling window of one minute to count page views per product. The result can be written directly to Azure SQL Database, enabling a live dashboard without additional orchestration.

Answer

Azure Data Factory

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Azure Synapse Pipelines

Answer

Azure Databricks

Question 12

A company is migrating a 2-TB on-premises SQL Server database to Azure. The database uses SQL Server Agent jobs for scheduled maintenance, relies on linked servers to query data from another SQL Server instance, and requires cross-database queries within the same instance. The company wants a fully managed PaaS service that minimizes application code changes and provides automatic backups and patching. Which Azure SQL service should they choose?

Accepted Answer

Azure SQL Managed Instance. Azure SQL Managed Instance is the correct choice because it provides near 100% compatibility with on-premises SQL Server, including support for SQL Server Agent jobs, linked servers, and cross-database queries within the same instance. As a fully managed PaaS service, it offers automatic backups, patching, and high availability while minimizing application code changes, unlike Azure SQL Database which lacks instance-scoped features.

Answer

Azure SQL Database (Single Database)

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Azure SQL Database (Elastic Pool)

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SQL Server on Azure Virtual Machine

Question 13

You need to design a data storage solution for an e-commerce platform that requires ACID transactions for order processing and high availability across regions. Which Azure service meets these requirements?

Accepted Answer

Azure SQL Database with active geo-replication. Azure SQL Database with active geo-region replication supports ACID transactions natively and provides automatic failover to a secondary region, ensuring high availability across regions. This meets the e-commerce platform's need for transactional consistency and regional resilience.

Answer

Azure Database for MySQL with read replicas

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Azure Synapse Analytics

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Azure Cosmos DB with multiple write regions

Question 14

A smart home company stores device telemetry in Azure Cosmos DB using the NoSQL API. Each document contains: deviceId (string), timestamp (datetime), temperature (float), humidity (float). The most common query retrieves all documents for a specific deviceId within a time range, ordered by timestamp descending. This query performs well. However, a new query that finds devices with temperature > 50 in the last hour (without specifying deviceId) is extremely slow and consumes many request units (RUs). What is the most likely cause?

Accepted Answer

The query does not specify the partition key (deviceId), causing a cross-partition query that scans every physical partition.. In Azure Cosmos DB NoSQL API, the partition key (deviceId) determines data distribution across physical partitions. Queries that do not include the partition key in the filter become cross-partition queries, which must fan out to every physical partition, scanning all documents. This is extremely slow and consumes many RUs, especially in large containers. The original query specifying deviceId performs well because it targets a single partition.

Answer

The temperature field is not indexed by default, so the query forces a full scan of all documents.

Answer

The time range filter on timestamp cannot be combined with the temperature filter efficiently.

Answer

The default indexing policy only indexes strings and numbers as range indexes, but temperature is stored as a number and is indexed.

Question 15

A company uses Azure Cosmos DB for a globally distributed application. They need to ensure low-latency reads and writes for users in multiple regions. Which consistency level provides the strongest guarantees without sacrificing availability?

Accepted Answer

Bounded staleness. Bounded staleness provides the strongest consistency guarantee that still maintains availability during a partition. It ensures that reads are guaranteed to be within a configurable staleness window (either K versions or a time interval) from the latest write, which is stronger than consistent prefix or eventual consistency, while avoiding the availability trade-offs of strong consistency in a globally distributed Azure Cosmos DB account.

Answer

Consistent prefix

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Strong

Answer

Eventual