DP-900 Korean exam dumps

Microsoft DP-900 Korean Value Package

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  • Exam Code: DP-900 Korean
  • Exam Name: Microsoft Azure Data Fundamentals (DP-900 Korean Version)
  • No. of Questions: 332 Questions and Answers
  • Updated: Oct 09, 2026

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  • Total Questions: 332
  • Updated on: Oct 09, 2026
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  • Total Questions: 332
  • Updated on: Oct 09, 2026
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  • Total Questions: 332
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Microsoft DP-900 exam comprises of multiple-choice questions that will test the candidate's knowledge of various data concepts in the Azure environment. DP-900-KR exam is timed and the candidate is given two hours to complete the test. The scoring is done on a scale of 0-1000 and the passing score for the exam is 700.

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Microsoft DP-900, also known as the Microsoft Azure Data Fundamentals Certification Exam, is an entry-level certification exam that validates the basic knowledge and understanding of cloud data services and Azure data services. DP-900-KR exam is designed for individuals who are interested in pursuing a career in data and want to demonstrate their competence in Azure data services. DP-900-KR exam is ideal for aspiring data analysts, data scientists, data engineers, or data architects who are looking to validate their knowledge and skillset in Azure data services.

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

The Microsoft DP-900-KR exam is ideal for data professionals, database administrators, and business intelligence developers who want to gain a fundamental understanding of Azure data services. It is also suitable for individuals who are interested in learning how to use Azure data services to solve business problems and improve decision-making processes.

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Microsoft DP-900 Korean Exam Syllabus Topics:

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

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