DP-900 Practice Questions 2 — 50 Questions

Question 1

A company updates a customer's address in a database. The update must ensure that all existing orders still reference a valid customer ID. The database checks the foreign key constraint and rejects the update if it would violate referential integrity. Which ACID property does this enforcement represent?

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

Accepted Answer

Consistency. Consistency ensures that any database transaction brings the database from one valid state to another, preserving all defined rules, including constraints like foreign keys. In this scenario, the foreign key constraint enforcement prevents an update that would leave orphaned order records, directly upholding the consistency property by rejecting the transaction if it violates referential integrity.

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Atomicity

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Isolation

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Durability

Question 2

A large e-commerce company needs to build an analytics solution. They have streaming clickstream data from their website (JSON) and daily sales data from their transactional database (CSV). They need to perform real-time dashboards on clickstream for the current hour, and also run complex historical queries that join sales data with aggregated clickstream data over the past year. They want a single Azure service that can handle both stream processing and batch processing using a unified experience, without moving data between separate systems. Which Azure service should they use?

Accepted Answer

Azure Synapse Analytics. Azure Synapse Analytics is the correct choice because it provides a unified experience for both stream processing (via Synapse Pipelines or Spark Structured Streaming) and batch processing (via dedicated SQL pools or serverless SQL), enabling real-time dashboards on clickstream data and complex historical queries joining sales data with aggregated clickstream data without moving data between separate systems.

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Azure Stream Analytics

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Azure Data Factory

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Azure HDInsight

Question 3

A manufacturing company collects real-time temperature data from thousands of IoT sensors. They need to build an analytics solution that processes the streaming data, computes the average temperature per device every minute, and outputs the results to a Power BI dashboard for near real-time visualization. Which Azure service should they use for the real-time stream processing?

Accepted Answer

Azure Stream Analytics. Azure Stream Analytics is the correct choice because it is a fully managed, real-time stream processing engine designed specifically for scenarios like this: ingesting high-velocity data from IoT sensors, performing time-windowed aggregations (e.g., average temperature per device every minute), and outputting results directly to Power BI for near real-time dashboards. It natively supports SQL-like query language for defining windowed computations and has built-in connectors for both IoT Hub/Event Hubs (input) and Power BI (output), making it the most efficient and purpose-built service for this streaming analytics workload.

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Azure Data Factory

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Azure Databricks

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Azure SQL Database

Question 4

A retail company receives real-time data from IoT sensors in its warehouses. Each sensor sends a JSON payload containing a device ID, timestamp, and temperature reading. A data engineer needs to classify this data for storage planning. Which data type best describes the JSON payload?

Accepted Answer

Semi-structured data. The JSON payload is considered semi-structured data because it has organizational properties (key-value pairs, nested structure) that provide a schema, but it does not conform to a rigid tabular schema like a relational database. JSON allows flexible fields and varying data types, which is characteristic of semi-structured data.

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Structured data

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Unstructured data

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Relational data

Question 5

An e-commerce company has 20 SQL Server databases that each range from 10 GB to 50 GB and experience unpredictable usage patterns with occasional spikes in user activity. The company wants to migrate to Azure SQL Database to reduce management overhead and minimize costs by allowing databases to share resources. Which Azure SQL Database deployment option should they choose?

Accepted Answer

B: Elastic pool. Elastic pools allow multiple SQL databases to share a fixed set of resources (eDTUs or vCores), which is ideal for databases with unpredictable usage patterns and occasional spikes. By pooling resources, the company can reduce management overhead and minimize costs compared to provisioning each database individually, as the pool's total resources are shared among all databases, smoothing out peak demands.

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A: Single database with provisioned throughput

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C: Managed Instance

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D: SQL Server on Azure VM

Question 6

A media company stores large video files in Azure Blob Storage. The videos are accessed frequently for the first 30 days after upload, then rarely for the next 180 days. After that, they are only needed for compliance and are never accessed. Which access tier should be used for the first 30 days to minimize costs while maintaining low latency?

Accepted Answer

Hot tier. The Hot tier is the correct choice for the first 30 days because it provides the lowest latency access and highest throughput for frequently accessed data, which matches the requirement of frequent access during this period. While the Hot tier has the highest storage cost per GB, it has no retrieval costs, making it cost-effective for high-access patterns. The other tiers introduce either retrieval fees (Cool), high latency (Archive), or unnecessary cost (Premium) for this use case.

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Cool tier

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Archive tier

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Premium tier

Question 7

A hospital collects patient vital signs every minute using IoT sensors. Each reading contains a timestamp, patient ID, heart rate, blood pressure, and temperature. This data is ingested continuously for real-time monitoring and alerting. Which type of data workload does this scenario best represent?

Accepted Answer

D. Real-time streaming. This scenario requires continuous ingestion of sensor data with immediate processing for real-time monitoring and alerting. Real-time streaming workloads, such as those handled by Azure Stream Analytics or Apache Kafka, are designed to process unbounded data streams with low latency, making option D correct.

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A. Transactional workload

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B. Analytical workload

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C. Batch processing

Question 8

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 9

A data analyst needs to create an interactive report that combines sales data from Azure SQL Database and Azure Cosmos DB. The report must refresh daily. Which tool should they use?

Accepted Answer

Power BI. Power BI is the correct tool because it is designed for creating interactive reports and dashboards, and it can directly connect to both Azure SQL Database and Azure Cosmos DB as data sources. Its scheduled refresh capability allows the report to refresh daily without manual intervention, meeting the requirement for an interactive, combined report.

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Azure Data Factory

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Azure Synapse Studio

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Azure Analysis Services

Question 10

A retail application uses Azure SQL Database. The Products table contains 200,000 rows with columns: ProductID (primary key, clustered), CategoryID, ProductName, Price, StockQuantity. Queries frequently filter on CategoryID and then sort results by Price in descending order. Which indexing strategy will most improve query performance for these operations?

Accepted Answer

Create a nonclustered index on (CategoryID, Price) with Price in descending order.. Creates a composite nonclustered index on (CategoryID, Price DESC) that directly supports both the filter (CategoryID equality) and the sort (Price descending) in a single index seek and ordered scan, eliminating the need for a separate sort operation. This is the most efficient strategy because the index is ordered exactly as the query requires, allowing SQL Server to retrieve matching rows in the correct order without additional processing.

Answer

Create a clustered index on CategoryID.

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Create a nonclustered index on CategoryID that includes Price as an included column.

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Create a clustered columnstore index on the table.

Question 11

A bank processes online fund transfers. Each transaction must ensure that either both the debit from the sender's account and the credit to the receiver's account occur, or if any part fails, the entire transaction is rolled back. Which ACID property does this guarantee?

Accepted Answer

Atomicity. Atomicity ensures that a transaction is treated as a single, indivisible unit of work. In this fund transfer scenario, atomicity guarantees that both the debit and credit operations either complete successfully together or are fully rolled back if any part fails, preventing partial updates that could leave the system in an inconsistent state.

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Consistency

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Isolation

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Durability

Question 12

A mobile game developer needs to store player session data. Each session has a unique SessionID, a UserID, a start timestamp, an end timestamp, and a collection of game events (each event is a JSON object). The application requires low-latency point reads by SessionID and the ability to query all sessions for a given UserID within a time range. The schema of game events can vary between sessions (e.g., new event types added frequently). The developer wants a fully managed NoSQL database that supports flexible schemas and secondary indexing. Which Azure data store should they choose?

Accepted Answer

Azure Cosmos DB with the NoSQL API. Azure Cosmos DB with the NoSQL API is the correct choice because it provides a fully managed, globally distributed NoSQL database with native support for flexible schemas (schemaless JSON documents), low-latency point reads by partition key (SessionID), and automatic secondary indexing for querying by UserID within a time range. Its ability to handle varying game event schemas without schema migrations makes it ideal for this use case.

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Azure Table Storage

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Azure Blob Storage

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Azure Cache for Redis

Question 13

A company uses Azure SQL Database for a reporting application. The database is mostly idle during weekdays but experiences heavy load on weekends when reports are generated. They want to minimize costs by only paying for compute resources when the database is active. Which Azure SQL Database pricing model should they choose?

Accepted Answer

Serverless. The Serverless pricing model for Azure SQL Database automatically pauses the database during periods of inactivity (e.g., weekdays) and resumes it when load increases (e.g., weekends), charging only for compute resources consumed during active periods. This aligns perfectly with the described workload pattern of mostly idle weekdays and heavy weekend usage, minimizing costs by eliminating charges for idle compute.

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Provisioned DTU

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Provisioned vCore

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Hyperscale

Question 14

A company stores large archives of legal documents in Azure Blob Storage. The documents must remain immutable; they cannot be modified or deleted for 7 years due to regulatory requirements. The data is accessed only for compliance audits, which occur less than once a year. The company wants to minimize storage costs while ensuring immutability and data durability. Which combination of features should they configure?

Accepted Answer

Archive access tier with a time-based retention policy. The Archive access tier provides the lowest storage cost for data that is rarely accessed, such as legal documents accessed less than once a year. A time-based retention policy enforces immutability for a fixed 7-year period, preventing modifications or deletions. This combination meets regulatory requirements while minimizing storage costs.

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Cool access tier with a time-based retention policy

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Hot access tier with versioning enabled

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Archive access tier with legal hold

Question 15

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 16

A company is migrating a SQL Server database to Azure SQL Database. The database uses CLR (Common Language Runtime) integration for business logic and has database mail configured. The company needs full instance-level functionality while still benefiting from the platform-as-a-service model. Which Azure SQL deployment option should they choose?

Accepted Answer

Azure SQL Managed Instance. Azure SQL Managed Instance is the correct choice because it provides near 100% compatibility with SQL Server on-premises, including support for CLR integration and Database Mail, while still offering a platform-as-a-service (PaaS) model. Single databases and elastic pools lack these instance-scoped features, and Hyperscale is a scaling option for single databases, not a separate deployment type that adds instance-level functionality.

Answer

Azure SQL Database (single database)

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Azure SQL Database elastic pool

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Azure SQL Database Hyperscale

Question 17

A logistics company stores sensor data from delivery trucks in Azure Table Storage. Each sensor reading includes a TruckID, Timestamp, Location, and EngineTemperature. The most common query retrieves all readings for all trucks within a specific one-hour time window (e.g., between 10:00 and 11:00 on a given day). Currently, the table uses PartitionKey = TruckID and RowKey = Timestamp (ISO format). However, queries filtering by time range are slow and consume many transactions. Which design change will most improve the performance of these time-range queries?

Accepted Answer

Change PartitionKey to a date-based value (e.g., YYYY-MM-DD) and RowKey to a composite of TruckID and Timestamp.. Azure Table Storage queries are most efficient when they target a specific PartitionKey and a range of RowKey values. By setting PartitionKey to a date-based value (e.g., YYYY-MM-DD), all readings for a given day are co-located in the same partition. Then, using a composite RowKey of TruckID and Timestamp allows the query to filter by time range within that partition using a single partition scan, drastically reducing the number of transactions and improving performance.

Answer

Change RowKey to be a composite of TruckID and Timestamp while keeping PartitionKey as TruckID.

Answer

Use Azure Cosmos DB with a partition key on Timestamp instead of Azure Table Storage.

Answer

Enable indexing on the Timestamp column in Azure Table Storage.

Question 18

A manufacturer collects sensor data from thousands of IoT devices every second. The data is ingested into Azure Event Hubs and then needs to be stored for historical analysis. The analytics team will run complex aggregations and time-series queries over petabytes of data, expecting fast results even with large scans. Which Azure service should be used as the analytical data store?

Accepted Answer

Azure Synapse Analytics dedicated SQL pool. Azure Synapse Analytics dedicated SQL pool is the correct choice because it is a massively parallel processing (MPP) engine designed for petabyte-scale data warehousing. It can run complex aggregations and time-series queries with fast results by distributing data across 60 distributions and using columnstore indexes for high compression and scan efficiency.

Answer

Azure Data Lake Storage Gen2

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Azure SQL Database

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Azure Cosmos DB

Question 19

A social media application displays the number of posts each user has created. After a user submits a new post, the count must reflect the update across all servers within a few seconds. Which data consistency model best describes this requirement?

Accepted Answer

Eventual consistency. Eventual consistency is correct because the requirement allows a few seconds for the update to propagate across all servers, meaning the system does not guarantee immediate uniformity but will converge to the same count eventually. This is typical in distributed systems like social media applications where high availability and partition tolerance are prioritized over immediate consistency, often using techniques like asynchronous replication.

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Strong consistency

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Sequential consistency

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Causal consistency

Question 20

A company is migrating a 3-TB on-premises SQL Server database to Azure. The database heavily uses cross-database queries with three-part names (e.g., db.schema.table) and relies on SQL Server Agent for scheduled maintenance jobs. They want a fully managed PaaS service with automatic backups and patching, while minimizing application code changes. 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 cross-database queries using three-part names (db.schema.table) and SQL Server Agent for scheduled maintenance jobs. 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 cross-database query support and SQL Agent.

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Azure SQL Database (single database)

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Azure SQL Database (elastic pool)

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Azure Synapse Analytics dedicated SQL pool