DP-900 Multiple Select — 30 Questions

Question 1

A company plans to migrate an on-premises SQL Server database to Azure. The database relies on SQL Agent jobs for nightly maintenance, uses Service Broker for asynchronous messaging, and requires high CPU and memory resources. The company wants to minimize application code changes. Which two Azure SQL deployment options meet all these requirements? (Choose two.)

Accepted Answer

Azure SQL Managed Instance. Azure SQL Managed Instance is correct because it provides near-100% compatibility with on-premises SQL Server, including SQL Agent jobs and Service Broker, while offering high CPU and memory resources. This minimizes application code changes by preserving existing features and configurations.

Answer

Azure SQL Database Single Database

Answer

Azure SQL Database Elastic Pool

Question 2

A globally distributed online auction platform uses a replicated database system across multiple Azure regions. The system must continue accepting bids (writes) even if a network partition occurs between regions, because auctions cannot be interrupted. The business decides that during a partition, some users might see slightly outdated item prices (read inconsistency) but all bids must be recorded. According to the CAP theorem, which two properties is this system prioritizing?

Accepted Answer

Availability (A) and Partition Tolerance (P). The system must continue accepting bids (writes) even during a network partition, which means it prioritizes Availability (A) — every request receives a response, even if it's not the most recent data. It also must function across multiple Azure regions that can become disconnected, which requires Partition Tolerance (P) — the system continues to operate despite network splits. The trade-off is that Consistency (C) is sacrificed, as users may see slightly outdated item prices during a partition. This is a classic AP (Availability and Partition Tolerance) choice from the CAP theorem.

Answer

Consistency (C) and Partition Tolerance (P)

Answer

Consistency (C) and Availability (A)

Question 3

Which TWO of the following are valid Azure data storage services for storing unstructured data?

Accepted Answer

Azure Blob Storage. Azure Blob Storage is a fully managed, massively scalable object storage service designed for unstructured data such as text, binary data, images, videos, and backups. It supports REST-based access and can store any type of file or binary object without requiring a schema, making it a core service for unstructured data workloads.

Answer

Azure SQL Database

Answer

Azure Table Storage

Answer

Azure Cosmos DB

Question 4

Which TWO of the following are common characteristics of a NoSQL database?

Accepted Answer

Flexible schema. Option A is correct because NoSQL databases, such as MongoDB or Cassandra, use a flexible schema that allows documents or records to have varying fields without requiring predefined table structures. This enables developers to iterate quickly and store semi-structured or unstructured data, such as JSON documents, without costly schema migrations.

Answer

Normalized data storage

Answer

Strong ACID transaction support

Answer

Relational data model

Question 5

Which THREE of the following are benefits of using a columnar storage format like Parquet for analytical workloads?

Accepted Answer

Reduced I/O when querying a subset of columns. Option B is correct because columnar storage formats like Parquet store data by column rather than by row. When a query only needs a subset of columns (e.g., SELECT SUM(sales) FROM table), the storage engine reads only the relevant column chunks from disk, dramatically reducing I/O compared to reading entire rows. This is a key performance advantage for analytical workloads that aggregate or filter on specific columns.

Answer

Enforced referential integrity constraints

Answer

Optimized for frequent row updates

Question 6

Which THREE factors should you consider when choosing between Azure SQL Database and Azure Cosmos DB for a new application? (Choose three.)

Accepted Answer

Schema flexibility. Option A is correct because Azure SQL Database requires a fixed relational schema, whereas Azure Cosmos DB is schema-agnostic and supports flexible, document-based data models. This makes Cosmos DB ideal for applications with evolving or unstructured data, while SQL Database suits strictly relational workloads.

Answer

Cost per GB

Answer

Maximum data size

Question 7

Which THREE are valid Azure data storage services that support semi-structured data?

Accepted Answer

Azure Cosmos DB. Azure Cosmos DB is a fully managed NoSQL database service that natively supports semi-structured data through its flexible schema model, allowing documents, key-value pairs, and graph data. It provides multiple APIs (SQL, MongoDB, Cassandra, Gremlin, and Table) to interact with semi-structured data, making it a valid choice for this question.

Answer

Azure SQL Database

Answer

Azure Data Lake Storage

Question 8

Which TWO Azure services can be used to perform data transformation in a data pipeline? (Choose two.)

Accepted Answer

Azure Databricks. Azure Databricks is correct because it provides an Apache Spark-based analytics platform that can perform complex data transformations, such as ETL (Extract, Transform, Load) operations, using notebooks and clusters. It allows you to write code in Python, Scala, or SQL to transform data at scale, making it a core compute service for data transformation in a pipeline.

Answer

Azure Blob Storage

Answer

Azure SQL Database

Answer

Azure Event Hubs

Question 9

Which TWO of the following Azure services are categorized as Platform as a Service (PaaS) for data storage?

Accepted Answer

Azure Cosmos DB. Azure Cosmos DB is a fully managed NoSQL database service that provides turnkey global distribution, elastic scaling, and multi-model support (document, key-value, graph, column-family). As a PaaS offering, it abstracts infrastructure management—such as hardware provisioning, patching, and replication—allowing developers to focus on data modeling and application logic.

Answer

Azure Synapse Analytics dedicated SQL pool

Answer

Azure Data Lake Storage Gen2

Answer

Azure Virtual Machines with SQL Server

Question 10

Which TWO data storage types are classified as structured data in Azure? (Choose two.)

Accepted Answer

Azure SQL Managed Instance. Azure SQL Managed Instance is a fully managed SQL Server database engine in Azure, which stores data in a relational schema with predefined tables, columns, and data types. This structured format enforces a rigid schema, making it a classic example of structured data storage in Azure.

Answer

Azure Cosmos DB

Answer

Azure Data Lake Storage

Answer

Azure Blob Storage

Question 11

Which TWO are advantages of using a NoSQL database like Azure Cosmos DB over a relational database like Azure SQL Database?

Accepted Answer

Flexible schema design. Option C is correct because NoSQL databases like Azure Cosmos DB are schema-agnostic, allowing each document or item to have a different structure without requiring migrations or predefined table schemas. This flexibility is ideal for rapidly evolving applications or when ingesting heterogeneous data, whereas Azure SQL Database enforces a rigid schema that must be defined and altered explicitly.

Answer

Support for complex joins

Answer

ACID transactions across multiple records

Answer

Enforced referential integrity

Question 12

Which TWO of the following are characteristics of structured data?

Accepted Answer

Data is organized in rows and columns. Structured data is defined by its organization into rows and columns, typically within a relational database or spreadsheet, where each column represents a specific attribute and each row a record. This tabular format enables efficient querying, sorting, and aggregation using SQL. Option B correctly identifies this core characteristic.

Answer

Data uses tags or markers to separate elements

Answer

Data is stored in Azure Cosmos DB

Answer

Data has no predefined schema

Question 13

Which TWO Azure services can be used to perform data transformation in a serverless manner? (Choose two.)

Accepted Answer

Azure Synapse serverless SQL pool. Azure Synapse serverless SQL pool (Option B) is correct because it allows you to query and transform data directly from data lake files (e.g., Parquet, CSV) using T-SQL without provisioning any dedicated compute resources. It uses a pay-per-query model, making it inherently serverless for data transformation tasks.

Answer

Azure Databricks with Apache Spark

Answer

Azure SQL Database

Answer

Azure HDInsight with Hive

Question 14

Which THREE are benefits of using a data warehouse in Azure?

Accepted Answer

Optimizes query performance for analytical workloads. A data warehouse in Azure (e.g., Azure Synapse Analytics) is optimized for analytical workloads through columnar storage and massively parallel processing (MPP), which significantly improves query performance on large datasets. This architecture is designed for read-heavy, aggregation-based queries typical of business intelligence and reporting, not for transactional or real-time operations.

Answer

Stores unstructured data like videos

Answer

Enables real-time streaming analytics

Question 15

Which TWO Azure services are designed for big data batch processing?

Accepted Answer

Azure Databricks. Azure Databricks is correct because it provides an Apache Spark-based analytics platform optimized for batch processing large datasets, enabling ETL, data transformation, and machine learning at scale. It uses distributed computing to process data in parallel across clusters, making it ideal for big data batch workloads.

Answer

Azure Data Explorer

Answer

Azure Stream Analytics

Answer

Azure Analysis Services

Question 16

Which THREE components are typically part of a modern data warehouse architecture on Azure? (Choose three.)

Accepted Answer

Azure Data Factory. Azure Data Factory is correct because it serves as the cloud-based ETL (Extract, Transform, Load) service that orchestrates and automates data movement and transformation across various sources and destinations. In a modern data warehouse architecture, Data Factory is used to ingest raw data from on-premises or cloud sources, transform it using mapping data flows or external compute (e.g., Azure Databricks), and load it into the data warehouse or data lake for analytics. It provides a code-free visual interface or SDK-based control for scheduling and monitoring pipelines, making it essential for the ingestion and preparation layer.

Answer

Azure Stream Analytics

Answer

Azure Cosmos DB

Question 17

Your company is designing a big data analytics solution on Azure. The solution must ingest streaming data from IoT devices, store the data in its raw format, and then use a distributed processing engine to transform the data before loading it into a serving layer for reporting. Which TWO Azure services should you include in the design?

Accepted Answer

Azure Event Hubs. Azure Event Hubs is a fully managed, real-time data ingestion service that can ingest millions of events per second from IoT devices. It is the correct choice for streaming data ingestion because it supports protocols like AMQP and HTTPS, and it decouples event producers from consumers, allowing the raw data to be captured and stored before processing.

Answer

Azure Blob Storage

Answer

Azure Data Factory

Answer

Azure Synapse Analytics

Question 18

Which TWO options are valid ways to ingest data into Azure Data Lake Storage Gen2?

Accepted Answer

AzCopy. AzCopy is a command-line utility designed specifically for copying data to and from Azure Blob Storage and Azure Data Lake Storage Gen2 using REST APIs. It supports high-performance, parallel transfers and can handle large datasets efficiently, making it a valid ingestion tool.

Answer

Power BI

Answer

Azure SQL Database

Answer

Azure DevOps

Question 19

Which THREE components are essential for building a real-time analytics solution on Azure?

Accepted Answer

Power BI. Power BI is correct because it serves as the visualization and reporting layer in a real-time analytics solution on Azure. It connects directly to Azure Stream Analytics or Event Hubs to render live dashboards and alerts, enabling users to monitor streaming data with sub-second latency.

Answer

Azure Data Lake Storage

Answer

Azure Analysis Services

Question 20

Which THREE components are part of a typical modern data warehouse architecture on Azure? (Choose three.)

Accepted Answer

Azure Synapse Analytics. Azure Synapse Analytics is a core component of a modern data warehouse architecture on Azure because it provides a unified analytics platform that combines big data and data warehousing capabilities. It enables T-SQL-based querying of both relational and non-relational data, integrating with Azure Data Lake Storage Gen2 for scalable storage and Azure Data Factory for orchestration.

Answer

Power BI

Answer

Azure Stream Analytics