Microsoft DP-900 Korean dumps - in .pdf

DP-900 Korean pdf
  • Exam Code: DP-900 Korean
  • Exam Name: Microsoft Azure Data Fundamentals (DP-900 Korean Version)
  • Updated: Sep 05, 2026
  • Q & A: 332 Questions and Answers
  • PDF Price: $69.99

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  • Exam Code: DP-900 Korean
  • Exam Name: Microsoft Azure Data Fundamentals (DP-900 Korean Version)
  • Updated: Sep 05, 2026
  • Q & A: 332 Questions and Answers
  • PDF Version + PC Test Engine + Online Test Engine
  • Value Pack Total: $139.98  $89.99
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Microsoft DP-900 Korean dumps - Testing Engine

DP-900 Korean Testing Engine
  • Exam Code: DP-900 Korean
  • Exam Name: Microsoft Azure Data Fundamentals (DP-900 Korean Version)
  • Updated: Sep 05, 2026
  • Q & A: 332 Questions and Answers
  • Software Price: $69.99
  • Testing Engine

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What is the duration, language, and format of Microsoft DP-900: Microsoft Azure Data Fundamentals Exam

  • This is the beta exam, would be available on or around March 31, 2020.
  • Number of Questions: 40 to 60 questions (Since Microsoft does not publish this information, the number of exam questions may change without notice.)
  • Language: English
  • Length of Examination: 50 mins
  • Passing score: 700 / 1000
  • Type of Questions: This test format is multiple choice.

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The Microsoft DP-900 (Microsoft Azure Data Fundamentals) is the single exam students will have to overcome if they want to attain the Microsoft Certified: Azure Data Fundamentals certificate. Those who hold this certification can become a developer, data engineer, data administrator, or data analyst.

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

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Microsoft DP-900 Korean Exam Syllabus Topics:

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

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