DP-900 Korean study materials - Microsoft DP-900 Korean dumps VCE

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

Exam Code: DP-900-KR

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

Updated: Aug 07, 2026

Q & A: 320 Questions and Answers

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Skills measured

  • Describe how to work with relational data on Azure (25-30%)
  • Describe core data concepts (15-20%)
  • Describe how to work with non-relational data on Azure (25-30%)
  • Describe an analytics workload on Azure (25-30%)

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

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The benefit of obtaining the Microsoft DP-900: Microsoft Azure Data Fundamentals Exam Certification

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Exam Details

The Microsoft DP-900 exam has the following features:

  • The registration for the test is done at Pearson VUE for non-students who are interested in technology and via Certiport for students or instructors.
  • It costs $99. As for the job seekers impacted by the pandemic (COVID -19), they can schedule their exam for just $15.
  • The number of questions is not disclosed but you should expect 40-60 items

Upon passing DP-900, you will earn the Microsoft Certified: Azure Data Fundamentals. It showcases that you have the foundational knowledge on core data concepts and how they can be implemented using Microsoft Azure. Note that Microsoft DP-900 will be updated on January 27, 2021.

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

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