Microsoft DP-900日本語 Q&A - in .pdf

  • Exam Code: DP-900日本語
  • Exam Name: Microsoft Azure Data Fundamentals (DP-900日本語版)
  • Updated: Aug 09, 2026
  • Q & A: 320 Questions and Answers
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  • Exam Code: DP-900日本語
  • Exam Name: Microsoft Azure Data Fundamentals (DP-900日本語版)
  • Updated: Aug 09, 2026
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Microsoft DP-900 (Microsoft Azure Data Fundamentals) Exam is a great entry-level certification for anyone who is looking to start a career in data management or data analytics. DP-900J exam covers a wide range of topics related to Azure data services, data storage options, data processing technologies, and data security. Microsoft Azure Data Fundamentals (DP-900日本語版) certification is a great starting point for anyone who is new to Azure data services and provides a solid foundation for anyone who is looking to pursue more advanced certifications in Azure data services.

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

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Microsoft DP-900 certification exam covers a range of topics related to data analytics and database administration, including core data concepts, relational and non-relational data, data storage options, data processing and transformation, and Azure data services. Candidates are expected to have a basic understanding of these concepts and technologies, as well as hands-on experience working with Azure data services.

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Microsoft DP-900日本語 Exam Syllabus Topics:

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

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