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  • Exam Code: DP-900-KR
  • Exam Name: Microsoft Azure Data Fundamentals (DP-900 Korean Version)
  • Last Updated: Sep 25, 2026
  • Q & A: 332 Questions and Answers
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  • Exam Code: DP-900-KR
  • Exam Name: Microsoft Azure Data Fundamentals (DP-900 Korean Version)
  • Last Updated: Sep 25, 2026
  • Q & A: 332 Questions and Answers
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Exam DP-900: Microsoft Azure Data Fundamentals

Candidates for this exam should have foundational knowledge of core data concepts and how they are implemented using Microsoft Azure data services.

This exam is intended for candidates beginning to work with data in the cloud.

Candidates should be familiar with the concepts of relational and non-relational data, and different types of data workloads such as transactional or analytical.

Azure Data Fundamentals can be used to prepare for other Azure role-based certifications like Azure Database Administrator Associate or Azure Data Engineer Associate, but it’s not a prerequisite for any of them.

Part of the requirements for: Microsoft Certified: Azure Data Fundamentals

Download exam skills outline

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

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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.

How to operate with relational data on Azure

Here, the candidate should be equipped with knowledge and skills in the following sub domains:

  • Identification of basic management roles for relational data – under this sub domain there are several skills covered that include the deployment and provisioning of relational data, various deployment methods such as Azure Resource Manager templates, Azure portal, Azure command-line interface (CLI), etc. Also, one should be knowledgeable in data components identification (authentication and firewall), the identification of basic connectivity problems such as accessing Azure VNets, firewalls, access from the internet and authentication). One more knowledge area involved is query tools (SQL Management Studio, Azure Data Studio, utility, sqlcmd etc.).
  • Relational data workloads – the candidate has to gain skills in identifying the appropriate data offerings when it comes to relational workload and learn more about structures of relational data.
  • Relational Azure data services – this section of the exam is focused on the following: the understanding of IaaS, SaaS and PaaS solutions and their comparison, Azure SQL DB services such as Azure SQL managed instance and Azure virtual machine, Azure Synapse Analytics, and Azure Database for MariaDB, PostgreSQL and for MySQL.
  • Data querying techniques that require utilizing SQL language – it deals with the Data Manipulation Language (DML) and Data Definition Language (DDL) as well as querying relational data on Azure SQL DB.

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Microsoft DP-900 Korean Exam Syllabus Topics:

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

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