Microsoft Azure Data Fundamentals: DP-900 Exam

"Microsoft Azure Data Fundamentals", also known as DP-900 exam, is a Microsoft Certification. With the complete collection of questions and answers, Pass4sureCert has assembled to take you through 332 Q&As to your DP-900 Exam preparation. In the DP-900 exam resources, you will cover every field and category in Microsoft Certified: Azure Data Fundamentals Certification helping to ready you for your successful Microsoft Certification.

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  • Exam Code: DP-900
  • Exam Name: Microsoft Azure Data Fundamentals
  • Certification Provider: Microsoft
  • Corresponding Certification: Microsoft Certified: Azure Data Fundamentals
  • Updated: Aug 22, 2026
  • No. of Questions: 332 Questions & Answers with Testing Engine
  • Download Limit: Unlimited

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Introduction to Microsoft DP-900: Microsoft Azure Data Fundamentals Exam

Microsoft Azure Data Fundamentals is an exam that identifies individuals who have the knowledge to work with Azure data storage features. Building on previous core principles of data management, Azure Data Fundamentals exam is designed to evaluate the ability of the candidate. Money designed to assess the skills level for both professionals and students. Determine the type of skills required for a particular situation, for example, a cloud administrator or a data analyst. Gen candidate will have to know the fundamentals of Data Management to work with Azure data storage, create tools to manage data, locate, protect and process it. Relevant topics in a data management environment, a certified candidate should understand. Dml, Db, protection tools through recovery, recovery strategies, documentation data management policies, data loss prevention tools to backup and recovery for backup recovery.

Explain the Techniques Involved in Working with Relational Data on Microsoft Azure: 25-30%

  • Explain the Query Methods for Data with the SQL Language: The learners should be capable of comparing the Data Manipulation Language with the Data Definition Language. They should also be able to query relational data within Azure Database for MySQL, Azure SQL Database, and Azure Database for PostgreSQL.
  • Explain the Concepts of Relational Data Workloads: The examinees should be able to explain the structures of relational data and identify the appropriate data for relational workloads.
  • Explain Relational Azure Data Services: The individuals should have the ability to explain and compare SaaS, PaaS, and IaaS solutions as well as Azure Synapse Analytics. They also need the knowledge of Azure SQL database services, Azure Database for PostgreSQL, Azure Database for MySQL, and Azure Database for MariaDB.
  • Identify the Fundamental Management Tasks for Relational Data: The applicants should be able to explain the deployment and provisioning of relational data services. They also need to understand the techniques for deployment, such as Azure Resource Manager templates, Azure portal, Azure CLI, and Azure PowerShell. In addition, the students should be able to identify the fundamental connectivity issues and components of data security.

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The candidates for the Microsoft DP-900 test will be measured in a variety of technical skill areas. These domains are divided into several topics. It is recommended that the applicants review the exam topics in detail and choose the appropriate study materials to prepare for the test. Below are the highlights of the objectives covered in this certification exam:

  • Explain Analytics Workloads on Azure: 25-30%

    This domain of the DP-900 exam measures one’s knowledge of analytics workloads, data processing, and ingestion on Azure, as well as the elements of modern data warehouses. The candidates will also be tested on their understanding of data visualization within Microsoft Power BI. This involves describing the specific role of dashboards, paginated reporting, interactive reports, and workflows in Power BI.

  • Explain the Concepts of Core Data: 15-20%

    Within this subject area, the students should be able to explain different categories of core data workloads that are available. To answer questions from this subtopic, the examinees should be able to explain batch data and streaming data. They should also know the attributes of relational data and core differences between streaming and batch data. It also covers their skills in core concepts of data analytics. This requires an understanding of data visualization, basic chart types, analytics techniques, data processing concepts, as well as ETL & ELT processing.

  • Explain how Non-Relational Data Works on Azure: 25-30%

    The questions from this section will evaluate the understanding of the candidates in non-relational data workloads as well as non-relational data contributions on Azure. They must be able to explain Azure File storage, Azure Cosmos DB APIs, Azure Blob Storage, and Azure Table storage. They should also be able to identify the foundational management tasks for non-relational data.

  • Explain how Relational Data Works on Azure: 25-30%

    The test takers will be required to have the ability to describe some concepts in this topic, including relational data workloads and relational Azure data services. They will also need to know how to identify the basic management functions for relational data. Additionally, they need to possess a good understanding of how to use the SQL language to describe the query methods for data.

Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/dp-900

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Microsoft DP-900 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Identify considerations for relational data on Azure20–25%- Describe Azure relational data services
  • 1. Open-source databases: PostgreSQL, MySQL, MariaDB
    • 2. Azure SQL Managed Instance
      • 3. SQL Server on Azure Virtual Machines
        • 4. Azure SQL Database
          - Describe relational data concepts
          • 1. Relationships, keys, constraints
            • 2. Normalization
              • 3. Query data with SQL
                Topic 2: Describe an analytics workload on Azure25–30%- Describe big data and analytics concepts
                • 1. Data ingestion and processing
                  • 2. Data lakes and data warehouses
                    • 3. Modern data warehouse architecture
                      - Describe real-time analytics
                      • 1. Stream processing concepts
                        • 2. Azure Stream Analytics
                          - Describe data visualization
                          • 1. Data models and reports
                            • 2. Power BI capabilities
                              - Describe Azure analytics services
                              • 1. Azure HDInsight
                                • 2. Azure Synapse Analytics
                                  • 3. Azure Data Lake Storage Gen2
                                    • 4. Azure Databricks
                                      • 5. Microsoft Fabric
                                        Topic 3: Describe core data concepts25–30%- Describe data workloads
                                        • 1. Transactional workloads
                                          • 2. Analytical workloads
                                            • 3. Batch and streaming data
                                              - Describe types of data
                                              • 1. File formats
                                                • 2. Structured, semi-structured, and unstructured data
                                                  - Describe roles and responsibilities
                                                  • 1. Data engineer, data analyst, database administrator
                                                    Topic 4: Describe considerations for working with non-relational data on Azure15–20%- Describe Azure Cosmos DB
                                                    • 1. Consistency levels and partitioning
                                                      • 2. APIs and data models
                                                        • 3. Capabilities and features
                                                          - Describe non-relational data concepts
                                                          • 1. Use cases for non-relational data
                                                            • 2. Characteristics of NoSQL data
                                                              - Describe Azure storage services
                                                              • 1. Queue Storage
                                                                • 2. Table Storage
                                                                  • 3. Blob Storage
                                                                    • 4. File Storage

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