Welcome to the Microsoft DP-900 Azure Data Fundamentals certification exam, the entrance to the fascinating world of Microsoft Azure data services and the world of fundamental data ideas. You get a special chance to show off your understanding of fundamental data ideas and how they apply to the robust data solutions provided by Azure in this test.
You will go on a trip to investigate both relational and non-relational data models as a candidate for this certification. Prepare to get fully immersed in the world of transactional and analytical data workloads as you learn about the unique functions and uses of each.
This exam is designed for individuals who are just beginning to work with data in the cloud, making it a perfect starting point for anyone seeking to deepen their understanding of data concepts and how they fit into the Azure ecosystem.
Microsoft DP-900 Certification Exam Questions and Answers
Whether you are a data enthusiast, a budding database administrator, or an aspiring data engineer, the DP-900 exam will equip you with the foundational knowledge you need to excel in the world of Azure data services.
Throughout your learning journey: You will encounter the fundamental concepts of relational and non-relational data, understanding their unique strengths and use cases. As you delve deeper, you will identify key considerations for leveraging these data models effectively on Azure, empowering you to make informed decisions for your data-driven projects.
The Azure Data Fundamentals: Exam not only prepares candidates for later certifications like Azure Database Administrator Associate or Azure Data Engineer Associate, but it also provides access to a wide range of data-related possibilities in the rapidly changing cloud environment.
So, are you prepared to go off on a unique data adventure? With the Microsoft DP-900 certification, get ready to unleash the enormous potential of Azure data services and strengthen your data knowledge. Together, let’s go on this thrilling trip and give your data-driven ambitions the wings they need to soar on the Azure cloud!
Microsoft DP-900 Certification Exam Questions and Answers
Beginner level:
Q1. Which term best describes data that is organized into rows and columns, where each row represents a unique record and each column represents an attribute or property of the record?
- A) NoSQL Data
- B) Relational Data
- C) Analytical Data
- D) Big Data
Correct Answer: B
Check out the Solution:
Relational data is structured data that is organized into tables with rows and columns. Each row represents a specific record, and each column represents a characteristic or attribute of the record.
Q2. What is the primary language used to interact with Azure SQL Database to manage relational data?
- A) Python
- B) JavaScript
- C) T-SQL (Transact-SQL)
- D) C#
Correct Answer: C
Check out the Solution:
T-SQL (Transact-SQL) is the primary language used to interact with Azure SQL Database and other SQL-based databases. It is a variant of SQL (Structured Query Language) and is used for managing and querying relational data.
Q3. Which type of NoSQL database model is best suited for storing vast amounts of unstructured or semi-structured data, such as text, images, and videos?
- A) Document Database
- B) Column-Family Database
- C) Key-Value Database
- D) Graph Database
Correct Answer: A
Check out the Solution:
Document databases are ideal for storing and managing unstructured or semi-structured data. They store data in JSON-like documents, making them suitable for scenarios involving text, images, videos, and other non-tabular data.
Q4. What is the purpose of Azure Synapse Analytics (formerly known as Azure SQL Data Warehouse)?
- A) Real-time data streaming and processing.
- B) Managing transactional data in real-time.
- C) Enabling big data processing and analysis.
- D) Providing real-time data visualization.
Correct Answer: C
Check out the Solution:
Azure Synapse Analytics is designed for big data processing and analysis. It enables users to perform complex data transformations, aggregations, and analytics on large volumes of data using SQL and Apache Spark.
Q5. Which type of data workload involves processing and analyzing data to gain insights and support decision-making?
- A) Transactional Data Workload
- B) Analytical Data Workload
- C) Big Data Workload
- D) Non-Relational Data Workload
Correct Answer: C
Check out the Solution:
Analytical data workloads involve processing and analyzing data to discover patterns, trends, and insights. These insights are used to support decision-making processes in various domains.
Intermediate Level:
Q1. What is the difference between structured and unstructured data?
- A) Structured data is organized, while unstructured data lacks any organization.
- B) Structured data is stored in NoSQL databases, while unstructured data is stored in relational databases.
- C) Structured data is in a fixed format, while unstructured data lacks a predefined structure.
- D) Structured data is easier to process and analyze than unstructured data.
Correct Answer: C
Check out the Solution:
Structured data is organized and follows a predefined format, often stored in tables or rows and columns. Unstructured data lacks a predefined structure, making it more flexible but challenging to analyze using traditional methods.
Q2. Which feature of Azure SQL Database provides automatic database backups and allows point-in-time recovery?
- A) Virtual Network Service Endpoints
- B) Azure Active Directory Integration
- C) Geo-Replication
- D) Azure SQL Database Automatic Tuning
Correct Answer: D
Check out the Solution:
Azure SQL Database Automatic Tuning provides automated database backups and allows point-in-time recovery, ensuring data protection and disaster recovery capabilities.
Q3. Which Azure service provides a fully-managed Apache Cassandra database-as-a-service?
- A) Azure Cosmos DB
- B) Azure HDInsight
- C) Azure Data Lake Analytics
- D) Azure Databricks
Correct Answer: A
Check out the Solution:
Azure Cosmos DB is a fully-managed NoSQL database service that provides support for Apache Cassandra, MongoDB, Gremlin, and more. It allows you to build globally distributed applications with ease.
Q4. Which Azure service is used to build and manage data pipelines for data integration and transformation?
- A) Azure Data Factory
- B) Azure Analysis Services
- C) Azure Stream Analytics
- D) Azure Logic Apps
Correct Answer: A
Check out the Solution:
Azure Data Factory is used to create, schedule, and manage data pipelines for data integration and transformation. It enables organizations to orchestrate and automate data workflows across various sources and destinations.
Q5. What is the primary purpose of data warehousing?
- A) Real-time data processing for analytical workloads.
- B) Secure storage of transactional data.
- C) Centralized storage and processing of historical data for analysis and reporting.
- D) Ensuring data consistency across different databases.
Correct Answer: C
Check out the Soultion:
Data warehousing is primarily used for centralized storage and processing of historical data. It enables organizations to perform complex analytics and reporting on large volumes of data efficiently.
Advance level:
Q1. Explain the CAP theorem in the context of distributed database systems.
- A) The CAP theorem states that a distributed database system can have only two of the three properties: Consistency, Availability, and Partition Tolerance. It means that in the event of a network partition, a system must choose between maintaining consistency or ensuring availability of data.
- B) The CAP theorem states that a distributed database system can have all three properties: Consistency, Availability, and Partition Tolerance. It guarantees that the system can maintain data consistency and availability even during network partitions.
- C) The CAP theorem states that a distributed database system can have either Consistency or Availability, but not both, in the presence of network partitions. It implies that the system needs to sacrifice either data consistency or data availability during network disruptions.
- D) The CAP theorem is not applicable to distributed database systems and only applies to single-node databases.
Correct Answer: A
Check out the Solution:
The CAP theorem states that a distributed database system can have only two of the three properties: Consistency, Availability, and Partition Tolerance. In the event of a network partition (communication failure between nodes), the system must choose between maintaining data consistency or ensuring data availability.
Q2. What are the advantages of using Azure SQL Database Managed Instance over Azure SQL Database Single Database?
- A) Azure SQL Database Managed Instance provides more features and advanced scalability options than Azure SQL Database Single Database. It is suitable for large-scale, mission-critical applications with complex requirements.
- B) Azure SQL Database Single Database offers better performance and lower latency compared to Azure SQL Database Managed Instance. It is ideal for small to medium-sized applications with less demanding workloads.
- C) Both Azure SQL Database Managed Instance and Azure SQL Database Single Database offer the same features and performance, but Managed Instance is more cost-effective for small-scale applications.
- D) Azure SQL Database Managed Instance is designed for offline data processing, while Azure SQL Database Single Database is optimized for real-time data processing.
Correct Answer: A
Check out the Solution:
Azure SQL Database Managed Instance provides more features and advanced scalability options compared to Azure SQL Database Single Database. It is well-suited for large-scale, mission-critical applications with complex requirements.
Q3. Which NoSQL database model is best suited for building social networking applications and representing relationships between entities?
- A) Document Database
- B) Key-Value Database
- C) Column-Family Database
- D) Graph Database
Correct Answer: D
Check out the Solution:
A graph database is best suited for building social networking applications and representing relationships between entities. It allows users to model, store, and query complex relationships with high efficiency.
Q4. Which Azure service provides a fully-managed Apache Spark-based analytics platform?
- A) Azure Data Factory
- B) Azure Stream Analytics
- C) Azure Databricks
- D) Azure Analysis Services
Correct Answer: C
Check out the Solution:
Azure Databricks is a fully-managed Apache Spark-based analytics platform in Azure. It enables data engineers and data scientists to collaborate and process big data at scale.
Q5. Explain the difference between OLTP (Online Transaction Processing) and OLAP (Online Analytical Processing) workloads.
- A) OLTP is designed for real-time data processing and is optimized for transactions and database updates. OLAP is designed for complex data analysis and reporting based on historical data.
- B) OLTP is suitable for real-time data streaming and analytics. OLAP is used for online data backups and restores.
- C) OLTP is optimized for data warehousing and complex data transformations. OLAP is designed for real-time data processing and rapid updates.
- D) OLTP and OLAP are two terms used interchangeably to describe the same type of workload in data processing.
Correct Answer: A
Check out the Solution:
OLTP (Online Transaction Processing) is designed for real-time data processing and is optimized for transactions and database updates. OLAP (Online Analytical Processing) is designed for complex data analysis and reporting based on historical data, such as data warehousing and data mining.
Q6. Explain the difference between horizontal partitioning and vertical partitioning in the context of database design.
- A) Horizontal partitioning divides a table’s rows into multiple partitions based on a specific column value, while vertical partitioning divides a table into multiple smaller tables based on specific row ranges.
- B) Horizontal partitioning divides a table into multiple smaller tables based on specific row ranges, while vertical partitioning divides a table’s rows into multiple partitions based on a specific column value.
- C) Horizontal partitioning and vertical partitioning are two terms used interchangeably to describe the same technique for dividing tables in a database.
- D) Horizontal partitioning and vertical partitioning are two different concepts unrelated to database design.
Correct Answer: A
Check out the Solution:
Horizontal partitioning divides a table’s rows into multiple partitions based on a specific column value, such as date or location, for efficient data retrieval and distribution. Vertical partitioning divides a table into multiple smaller tables, each containing a subset of the columns, to reduce data duplication and improve query performance.
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