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Microsoft DP-900日本語 : Microsoft Azure Data Fundamentals (DP-900日本語版)

DP-900日本語

Exam Code: DP-900J

Exam Name: Microsoft Azure Data Fundamentals (DP-900日本語版)

Updated: Aug 30, 2026

Q & A: 332 Questions and Answers

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Microsoft learning site Administer infrastructure resources in Azure Azure Storage Azure Network

Exam DP-900: Microsoft Azure Data Fundamentals

Candidates for this exam should have foundational knowledge of core data concepts and how they are implemented using Microsoft Azure data services.

This exam is intended for candidates beginning to work with data in the cloud.

Candidates should be familiar with the concepts of relational and non-relational data, and different types of data workloads such as transactional or analytical.

Azure Data Fundamentals can be used to prepare for other Azure role-based certifications like Azure Database Administrator Associate or Azure Data Engineer Associate, but it’s not a prerequisite for any of them.

Part of the requirements for: Microsoft Certified: Azure Data Fundamentals

Download exam skills outline

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

Microsoft DP-900日本語 Exam Syllabus Topics:

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

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