Microsoft Azure Data Fundamentals (DP-900 Korean Version) : DP-900 Korean

  • Exam Code: DP-900-KR
  • Exam Name: Microsoft Azure Data Fundamentals (DP-900 Korean Version)
  • Updated: Jul 19, 2026     Q & A: 320 Questions and Answers

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About Microsoft DP-900 Korean Exam

Microsoft DP-900 exam is a perfect fit for data professionals who are looking for a career in data analytics or data engineering. Microsoft Azure Data Fundamentals (DP-900 Korean Version) certification is an industry-standard that validates the candidates' foundational knowledge of core data concepts and their abilities in working with data services on the Azure platform. DP-900-KR exam is designed to be accessible to everyone, irrespective of their experience level, and provides a great opportunity for individuals to build their skills and advance their careers in the field of data analytics and engineering.

Microsoft DP-900 certification exam covers a range of topics related to cloud data services, including core concepts of Azure data services, relational and non-relational data offerings, and analytics services. It also covers data security, privacy, compliance, and pricing models for Azure data services. DP-900-KR exam is designed to test your knowledge of these topics and your ability to apply them in real-world scenarios.

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

Microsoft DP-900 (Microsoft Azure Data Fundamentals) certification exam provides individuals with a foundational knowledge of cloud data services in Microsoft Azure. It is a great starting point for beginners who are interested in learning about cloud data management and can be used to progress towards higher-level Azure certifications. With the right training and preparation, individuals can successfully pass the DP-900 exam and kickstart their career in cloud data management.

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The Microsoft DP-900-KR exam covers a wide range of topics related to Azure data services, including data storage options, data processing technologies, data analysis tools, and data security. Candidates are expected to have a basic understanding of databases, SQL, and programming concepts.

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Microsoft DP-900 Korean Exam Syllabus Topics:

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

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