If you’re preparing for the DP-900 certification exam or simply looking to expand your knowledge of Azure data concepts, you’ve come to the right place. In this blog, we will provide you with a set of free questions that cover the key topics and concepts included in the DP-900 exam. The DP-900 exam focuses on the fundamentals of Azure data services, providing a solid foundation for anyone working with data on the Azure platform.
By answering these questions, you can assess your understanding of core Azure data concepts and identify areas where you may need further study or practice. Whether you’re a data professional, a developer, or an IT enthusiast, this blog will serve as a valuable resource to enhance your understanding of Microsoft Azure’s data services. So let’s dive in and test your knowledge with these DP-900 free questions!
Section 1: Exploring Essential Data Concepts
This section provides an overview of core data concepts, covering various aspects such as data representation, structured and semi-structured data features, storage options, common data file formats, types of databases, and different data workloads. Additionally, it covers the characteristics of transactional and analytical workloads, as well as the roles and responsibilities involved in handling data workloads.
Topic: Ways to represent data
Question: Which of the following is a data representation method used to organize data into a collection of tables?
a) Hierarchical data model
b) Relational data model
c) Object-oriented data model
d) Key-value data model
The correct answer is b) Relational data model.
Explanation: The relational data model represents data in tables with rows and columns, and it establishes relationships between tables using keys.
For more: Concepts of relational data
Question: Which data representation method uses a tree-like structure with parent-child relationships?
a) Hierarchical data model
b) Relational data model
c) Object-oriented data model
d) Key-value data model
The correct answer is a) Hierarchical data model.
Explanation: The hierarchical data model organizes data in a tree-like structure with parent-child relationships, where each parent can have multiple children.
Question: Which data representation method stores data as objects that encapsulate both data and behavior?
a) Hierarchical data model
b) Relational data model
c) Object-oriented data model
d) Key-value data model
The correct answer is c) Object-oriented data model.
Explanation: The object-oriented data model represents data as objects that contain both data attributes and behavior methods.
For more: Common Data Model
Question: Which data representation method stores data as key-value pairs without a fixed schema?
a) Hierarchical data model
b) Relational data model
c) Object-oriented data model
d) Key-value data model
The correct answer is d) Key-value data model.
Explanation: The key-value data model stores data as simple key-value pairs, where the values can vary in structure and don’t require a fixed schema.
Topic: Options for data storage
Question: Which option provides a serverless data storage service in Azure that automatically scales and replicates data across multiple regions?
a) Azure Blob storage
b) Azure SQL Database
c) Azure Cosmos DB
d) Azure Data Lake Storage
The correct answer is c) Azure Cosmos DB.
Explanation: Azure Cosmos DB is a globally distributed, multi-model database service that provides automatic scaling, high availability, and low latency access to data.
For more: Azure Cosmos DB
Question: Which service is a highly scalable and secure object storage service in Azure, suitable for storing large amounts of unstructured data?
a) Azure Blob storage
b) Azure SQL Database
c) Azure Cosmos DB
d) Azure Data Lake Storage
The correct answer is a) Azure Blob storage.
Explanation: Azure Blob storage is a scalable and secure object storage service that is designed to store and serve large amounts of unstructured data.
For more: Azure Blob Storage
Question: Which option is a relational database service in Azure that offers managed instances and flexible deployment options?
a) Azure Blob storage
b) Azure SQL Database
c) Azure Cosmos DB
d) Azure Data Lake Storage
The correct answer is b) Azure SQL Database.
Explanation: Azure SQL Database is a fully managed relational database service in Azure that provides high availability, automatic patching, and backups.
For more: Azure SQL Database
Question: Which option is a distributed file system in Azure that is optimized for big data analytics workloads?
a) Azure Blob storage
b) Azure SQL Database
c) Azure Cosmos DB
d) Azure Data Lake Storage
The correct answer is d) Azure Data Lake Storage.
Explanation: Azure Data Lake Storage is a distributed file system that is designed for big data analytics workloads, allowing large-scale processing and analysis of data.
For more: Azure Data Lake Storage Gen2
Topic: Common data workloads
Question: Which data workload involves processing and analyzing large volumes of data to uncover patterns and insights?
a) Online transaction processing (OLTP)
b) Online analytical processing (OLAP)
c) Extract, Transform, Load (ETL)
d) Data warehousing
The correct answer is b) Online analytical processing (OLAP).
Explanation: OLAP involves processing and analyzing large volumes of data to support complex analytical queries, data mining, and business intelligence activities.
For more: Online analytical processing (OLAP)
Question: Which data workload focuses on handling high volumes of real-time transactional data, such as online retail transactions?
a) Online transaction processing (OLTP)
b) Online analytical processing (OLAP)
c) Extract, Transform, Load (ETL)
d) Data warehousing
The correct answer is a) Online transaction processing (OLTP).
Explanation: OLTP involves handling high volumes of real-time transactional data, such as inserting, updating, and deleting records in a database.
For more: Online transaction processing (OLTP)
Question: Which data workload involves extracting data from various sources, transforming it into a consistent format, and loading it into a target system?
a) Online transaction processing (OLTP)
b) Online analytical processing (OLAP)
c) Extract, Transform, Load (ETL)
d) Data warehousing
The correct answer is c) Extract, Transform, Load (ETL).
Explanation: ETL is a process that involves extracting data from multiple sources, transforming it into a consistent format, and loading it into a target system, typically a data warehouse.
For more: Extract, Transform, Load (ETL)
Question: Which workload involves storing large amounts of structured and historical data to support reporting and analysis?
a) Online transaction processing (OLTP)
b) Online analytical processing (OLAP)
c) Extract, Transform, Load (ETL)
d) Data warehousing
The correct answer is d) Data warehousing.
Explanation: Data warehousing involves storing large amounts of structured and historical data in a central repository to facilitate reporting, analysis, and decision-making processes.
For more: Data warehousing
Topic: Roles and responsibilities for data workloads
Question: Which role is responsible for designing and implementing the structure and organization of a database?
a) Database administrator (DBA)
b) Data analyst
c) Data Engineer
d) Data scientist
The correct answer is a) Database administrator (DBA).
Explanation: A DBA is responsible for designing and implementing the structure and organization of a database, managing its performance, and ensuring data integrity.
Question: Which role is responsible for analyzing and interpreting data to derive meaningful insights and support decision-making?
a) Database administrator (DBA)
b) Data analyst
c) Data engineer
d) Data scientist
The correct answer is b) Data analyst.
Explanation: A data analyst is responsible for analyzing and interpreting data, creating reports and visualizations, and providing insights to support business decision-making processes.
Question: Which role is responsible for developing and maintaining data pipelines and workflows to transform and move data between systems?
a) Database administrator (DBA)
b) Data analyst
c) Data engineer
d) Data scientist
The correct answer is c) Data engineer.
Explanation: A data engineer is responsible for developing and maintaining data pipelines and workflows, including data extraction, transformation, and loading processes.
Question: Which role is responsible for applying advanced analytics techniques, machine learning, and statistical models to extract insights from data?
a) Database administrator (DBA)
b) Data analyst
c) Data engineer
d) Data scientist
The correct answer is d) Data scientist.
Explanation: A data scientist is responsible for applying advanced analytics techniques, machine learning algorithms, and statistical models to extract insights from data and develop predictive or prescriptive models.
Section 2: Understanding Relational Data on Azure
This section explores important considerations for managing relational data on the Azure cloud platform. It covers relational concepts and highlights the features of relational data. Additionally, it explains the concept of normalization and its significance in database design. The topic also provides an overview of common SQL statements and database objects.
Furthermore, it covers relational Azure data services, focusing on the Azure SQL family of products, including Azure SQL Database, Azure SQL Managed Instance, and SQL Server on Azure Virtual Machines.
Topic: Relational concepts
Question: What is a primary key in a relational database?
a) It is a unique identifier for a table in a database.
b) It is a field that defines the relationships between tables.
c) It is a field or combination of fields that uniquely identifies a record in a table.
d) It is a set of rules that enforce data integrity in a database.
The correct answer is c) It is a field or combination of fields that uniquely identifies a record in a table.
Explanation: A primary key in a relational database ensures that each record in a table is uniquely identifiable.
For more: Primary key, foreign key, and unique key
Question: What is a foreign key in a relational database?
a) It is a unique identifier for a table in a database.
b) It is a field that defines the relationships between tables.
c) It is a field or combination of fields that uniquely identifies a record in a table.
d) It is a set of rules that enforce data integrity in a database.
The correct answer is b) It is a field that defines the relationships between tables.
Explanation: A foreign key in a relational database establishes a link between two tables by referencing the primary key of another table.
For more: Create Foreign Key Relationships
Question: What is a table relationship in a relational database?
a) It is a unique identifier for a table in a database.
b) It is a field that defines the relationships between tables.
c) It is a field or combination of fields that uniquely identifies a record in a table.
d) It is a set of rules that enforce data integrity in a database.
The correct answer is b) It is a field that defines the relationships between tables.
Explanation: A table relationship specifies how two tables are connected through their keys to establish data associations.
For more: Table relationship in a relational database
Question: What is normalization in the context of relational databases?
a) It is a process of organizing data into tables and defining relationships between them.
b) It is a process of removing duplicate data from a database.
c) It is a process of storing data in a denormalized format for faster access.
d) It is a process of backing up a database to ensure data availability.
The correct answer is a) It is a process of organizing data into tables and defining relationships between them.
Explanation: Normalization is a database design technique that minimizes data redundancy and ensures data integrity by organizing data into logical tables.
For more: Relational database
Topic: Relational Azure data services
Question: Which Azure service is a fully managed relational database service that supports multiple database engines, including SQL Server, MySQL, and PostgreSQL?
a) Azure Cosmos DB
b) Azure SQL Database
c) Azure Database for MySQL
d) Azure Database for PostgreSQL
The correct answer is b) Azure SQL Database.
Explanation: Azure SQL Database is a fully managed relational database service in Azure that supports multiple database engines and provides high availability, automatic backups, and scalability.
For more: Azure SQL Database
Question: Which Azure service is a globally distributed, multi-model database service that supports both document and key-value data models?
a) Azure Cosmos DB
b) Azure SQL Database
c) Azure Database for MySQL
d) Azure Database for PostgreSQL
The correct answer is a) Azure Cosmos DB.
Explanation: Azure Cosmos DB is a globally distributed, multi-model database service that supports multiple data models, including document, key-value, graph, and column-family.
For more: Azure Cosmos DB
Question: Which Azure service provides a fully managed MySQL database service in Azure with built-in high availability and scalability?
a) Azure Cosmos DB
b) Azure SQL Database
c) Azure Database for MySQL
d) Azure Database for PostgreSQL
The correct answer is c) Azure Database for MySQL.
Explanation: Azure Database for MySQL is a fully managed MySQL database service in Azure that provides high availability, automated backups, and flexible scalability.
For more: Azure Database for MySQL
Question: Which Azure service provides a fully managed, globally distributed relational database service that offers horizontal scale-out capability?
a) Azure Cosmos DB
b) Azure SQL Database
c) Azure Database for MySQL
d) Azure Database for PostgreSQL
The correct answer is a) Azure Cosmos DB.
Explanation: Azure Cosmos DB is a globally distributed database service that supports multiple data models, including a document model, and allows for horizontal scale-out to handle high volumes of traffic.
For more: Azure Cosmos DB
Question: Which Azure service is an open-source relational database management system that provides high availability, scalability, and compatibility with SQL Server?
a) Azure Cosmos DB
b) Azure SQL Database
c) Azure Database for MySQL
d) Azure Database for PostgreSQL
The correct answer is d) Azure Database for PostgreSQL.
Explanation: Azure Database for PostgreSQL is an open-source relational database management system that offers high availability, scalability, and compatibility with SQL Server.
For more: Azure Database for PostgreSQL
Section 3: Exploring Considerations for Non-Relational Data on Azure
This section focuses on considerations for working with non-relational data on the Azure cloud platform. It begins by describing the capabilities of Azure storage, including Azure Blob storage, Azure File storage, and Azure Table storage. It highlights the features and uses cases of each storage option.
The topic also covers Azure Cosmos DB, a globally-distributed, multi-model database service. It explores the capabilities and features of Azure Cosmos DB, emphasizing its flexibility in handling various data models and workloads.
Topic: Capabilities of Azure storage
Question: Which Azure storage service is designed to store and retrieve large amounts of unstructured data, such as documents, images, and videos?
a) Azure Blob storage
b) Azure File storage
c) Azure Queue storage
d) Azure Table storage
The correct answer is a) Azure Blob storage.
Explanation: Azure Blob storage is specifically designed to store and retrieve unstructured data, making it suitable for storing documents, images, videos, and other binary large objects (BLOBs).
For more: Azure Blob Storage
Question: Which Azure storage service provides shared storage for applications using the standard SMB or NFS protocols?
a) Azure Blob storage
b) Azure File storage
c) Azure Queue storage
d) Azure Table storage
The correct answer is b) Azure File storage.
Explanation: Azure File storage offers shared storage for applications using the standard Server Message Block (SMB) or Network File System (NFS) protocols.
For More: Azure Files
Question: Which Azure storage service is a simple message queue service used for reliable messaging between application components?
a) Azure Blob storage
b) Azure File storage
c) Azure Queue storage
d) Azure Table storage
The correct answer is c) Azure Queue storage.
Explanation: Azure Queue storage is a simple message queue service that enables reliable messaging and asynchronous communication between different components of an application.
For More: Azure Queue storage
Question: Which Azure storage service provides NoSQL storage with key-value pairs and is suitable for storing large amounts of structured data?
a) Azure Blob storage
b) Azure File storage
c) Azure Queue storage
d) Azure Table storage
The correct answer is d) Azure Table storage.
Explanation: Azure Table storage is a NoSQL storage service that stores data as key-value pairs, making it suitable for storing large amounts of structured data.
For More: Azure Table storage
Topic: Capabilities and features of Azure Cosmos DB
Question: What is a major advantage of Azure Cosmos DB?
a) It is a relational database service with ACID compliance.
b) It provides automatic scaling and global distribution capabilities.
c) It offers built-in support for serverless computing.
d) It has a fixed schema that ensures data consistency.
The correct answer is b) It provides automatic scaling and global distribution capabilities.
Explanation: Azure Cosmos DB is a globally distributed database service that offers automatic scaling, allowing it to handle high traffic volumes and provide low-latency access to data from any geographical location.
For more: Azure Cosmos DB
Question: Which data models are supported by Azure Cosmos DB?
a) Only document data model
b) Only key-value data model
c) Document, key-value, column-family, and graph data models
d) Only column-family data model
The correct answer is c) Document, key-value, column-family, and graph data models.
Explanation: Azure Cosmos DB supports multiple data models, including document, key-value, column-family, and graph, providing flexibility to choose the most suitable model for the application’s needs.
For more: Azure Cosmos DB
Question: Which consistency levels are available in Azure Cosmos DB?
a) Strong, eventual, bounded staleness, and session consistency
b) Strong, weak, optimistic, and eventual consistency
c) Immediate, eventual, strong, and eventual consistency
d) Strong, eventual, optimistic, and session consistency
The correct answer is a) Strong, eventual, bounded staleness, and session consistency.
Explanation: Azure Cosmos DB provides different consistency levels to meet various application requirements, including strong, eventual, bounded staleness, and session consistency.
For more: Azure Cosmos DB
Question: Which feature in Azure Cosmos DB allows developers to perform SQL-like queries on JSON documents?
a) DocumentDB API
b) Cassandra API
c) Gremlin API
d) Table API
The correct answer is a) DocumentDB API.
Explanation: The DocumentDB API in Azure Cosmos DB allows developers to perform SQL-like queries on JSON documents, making it easier to work with structured and semi-structured data.
For More: Document Class
Question: Which API in Azure Cosmos DB allows developers to use Gremlin graph traversal language for querying and analyzing graph data?
a) DocumentDB API
b) Cassandra API
c) Gremlin API
d) Table API
The correct answer is c) Gremlin API.
Explanation: The Gremlin API in Azure Cosmos DB enables developers to use the Gremlin graph traversal language for querying and analyzing graph data, making it suitable for graph database scenarios.
For More: Azure Cosmos DB for Apache Gremlin
Question: Which API in Azure Cosmos DB provides compatibility with Apache Cassandra and allows developers to use Cassandra Query Language (CQL)?
a) DocumentDB API
b) Cassandra API
c) Gremlin API
d) Table API
The correct answer is b) Cassandra API.
Explanation: The Cassandra API in Azure Cosmos DB provides compatibility with Apache Cassandra and allows developers to use Cassandra Query Language (CQL) to interact with data, making it suitable for Cassandra-based applications.
For More: Azure Cosmos DB for Apache Cassandra
Section 4: Exploring Analytics Workloads on Azure
This topic provides an in-depth understanding of analytics workloads on the Azure cloud platform. It begins by describing the common elements of large-scale analytics, covering aspects such as data ingestion and processing considerations. It further explores the options available for analytical data stores, emphasizing their role in supporting efficient data analysis.
You will get to learn about Azure services specifically designed for data warehousing, including Azure Synapse Analytics, Azure Databricks, Azure HDInsight, and Azure Data Factory. Additionally, it discusses the considerations for real-time data analytics, distinguishing between batch and streaming data processing approaches.
Topic: Common elements of large-scale analytics
Question: What is the primary objective of large-scale analytics?
a) Real-time data processing
b) Historical data analysis
c) Predictive modeling
d) Data visualization
The correct answer is b) Historical data analysis.
Explanation: Large-scale analytics focuses on analyzing historical data to gain insights, identify patterns, and make informed decisions based on past trends and observations.
For more: Manage historical analytics reports in Customer Service
Question: Which component is responsible for collecting and storing large volumes of data for analytics purposes?
a) Data warehouse
b) Data visualization tool
c) Data pipeline
d) Data lake
The correct answer is d) Data lake.
Explanation: A data lake is a storage repository that stores large amounts of raw and unprocessed data from various sources, providing a centralized location for analytics and data exploration.
For more: Azure Data Lake Storage Gen2
Question: What is the purpose of data preprocessing in large-scale analytics?
a) To clean and transform raw data into a usable format
b) To aggregate and summarize data for faster processing
c) To visualize data using charts and graphs
d) To train machine learning models on labeled data
The correct answer is a) To clean and transform raw data into a usable format.
Explanation: Data preprocessing involves cleaning, transforming, and organizing raw data to remove inconsistencies, handle missing values, and prepare it for analysis.
Question: Which technique is commonly used in large-scale analytics to discover hidden patterns and insights in data?
a) Regression analysis
b) Clustering analysis
c) Hypothesis testing
d) Data visualization
The correct answer is b) Clustering analysis.
Explanation: Clustering analysis is a technique used in large-scale analytics to group similar data points together, allowing for the discovery of patterns, similarities, and relationships within the data.
For more: Microsoft Clustering Algorithm
Topic: Considerations for real-time data analytics
Question: What is the primary advantage of real-time data analytics?
a) Immediate insights and decision-making
b) Historical trend analysis
c) Predictive modeling accuracy
d) Data visualization capabilities
The correct answer is a) Immediate insights and decision-making.
Explanation: Real-time data analytics enables organizations to analyze and act upon data as it is generated, providing immediate insights and the ability to make faster and more informed decisions.
Question: Which technology is commonly used for real-time data streaming and processing in Azure?
a) Apache Kafka
b) Azure Data Factory
c) Azure Data Lake Analytics
d) Azure Stream Analytics
The correct answer is d) Azure Stream Analytics.
Explanation: Azure Stream Analytics is a real-time event processing service in Azure that enables the ingestion, processing, and analysis of streaming data from various sources, such as IoT devices, sensors, and social media feeds.
For more: Azure Stream Analytics
Question: What is the primary purpose of complex event processing (CEP) in real-time data analytics?
a) Data visualization and reporting
b) Batch processing of historical data
c) Real-time detection of patterns and anomalies
d) Machine learning model training
The correct answer is c) Real-time detection of patterns and anomalies.
Explanation: Complex event processing (CEP) is a technique used in real-time data analytics to detect complex patterns and correlations in streaming data, enabling immediate actions or alerts to be triggered based on predefined rules.
Question: Which Azure service enables real-time data visualization and exploration of streaming data?
a) Azure Synapse Analytics
b) Azure Data Factory
c) Azure Data Explorer
d) Azure Machine Learning
The correct answer is c) Azure Data Explorer.
Explanation: Azure Data Explorer is a fast and highly scalable data exploration and visualization service in Azure that supports real-time analytics and interactive querying of large volumes of streaming and historical data.
For more: Azure Data Explorer
Topic: Data visualization in Microsoft Power BI
Question: What is the primary purpose of data visualization in analytics?
a) To communicate data insights effectively
b) To store and organize data for analysis
c) To preprocess and clean raw data
d) To train machine learning models
The correct answer is a) To communicate data insights effectively.
Explanation: Data visualization plays a crucial role in analytics by presenting data in a visual format, such as charts, graphs, and dashboards, to facilitate understanding, identify patterns, and communicate insights to stakeholders.
For more: Data visualization with Azure Data Explorer
Question: Which Azure service is commonly used for creating interactive and visually appealing data visualizations?
a) Azure Synapse Analytics
b) Azure Data Factory
c) Azure Data Explorer
d) Power BI
The correct answer is d) Power BI.
Explanation: Power BI is a business analytics service by Microsoft that enables users to create interactive dashboards, reports, and data visualizations, allowing for data exploration and sharing insights across the organization.
For more: Power BI
Final Words
We hope that these free questions for the Microsoft Azure Data Fundamentals (DP-900) certification exam have been valuable in your preparation and knowledge expansion. By engaging with these questions, you have had the opportunity to test your understanding of core Azure data concepts and identify areas for further study or practice.
Remember, the DP-900 exam focuses on the fundamental principles of Azure data services, providing a solid foundation for working with data on the Azure platform. By mastering these concepts, you will be well-equipped to leverage Azure’s data services effectively.
We encourage you to continue your learning journey and explore additional resources, such as official documentation, online courses, and hands-on experience, to deepen your understanding of Microsoft Azure’s data services.
