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Last Updated: Aug 25, 2026

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Microsoft DP-900 Practice Test Questions, Microsoft DP-900 Exam Practice Test Questions

The Microsoft DP-900 exam is a qualifying test for obtaining the Microsoft Certified: Azure Data Fundamentals certification. This exam is intended for the entry-level professionals looking to take up a career path in the IT field. Although it is not a requirement for any advanced-level certificate, the DP-900: Microsoft Azure Data Fundamentals test is a great foundation to prepare the individuals for other Azure role-based options. Thus, the certified candidates can pursue two certifications: Azure Data Engineer Associate or Azure Database Administrator Associate.

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 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.

  • 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 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.

The old saying "There is no royal road to learning" is now obsolete, since with the development of science and technology, we can resort to electronic DP-900 Korean exam materials, which is now a commonplace, and the electronic materials with the highest quality which consists of all of the key points required for the exam can really be considered as the royal road to learning. Fortunately, the DP-900 Korean practice test: Microsoft Azure Data Fundamentals (DP-900 Korean Version) compiled by our company are the best choice for you, you just lucky enough to click into this website, since you are sure to pass the exam as well as getting the related certification under the guidance of our DP-900 Korean study guide which you can find in this website easily. Now, I would like to introduce some of the detailed information about our training materials for your reference.

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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.

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

Microsoft DP-900 Korean Exam Syllabus Topics:

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

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