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

  • Exam Code: DP-900日本語
  • Exam Name: Microsoft Azure Data Fundamentals (DP-900日本語版)
  • Updated: Aug 16, 2026

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Microsoft Azure Data Fundamentals Exam Certification Details:

Exam CodeDP-900
Exam Price$99 (USD)
Schedule ExamPearson VUE
Books / TrainingDP-900T00-A: Microsoft Azure Data Fundamentals
Number of Questions40-60
Passing Score700 / 1000
Duration60 mins
Exam NameMicrosoft Certified - Azure Data Fundamentals
Sample QuestionsMicrosoft Azure Data Fundamentals Sample Questions

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

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

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Microsoft DP-900日本語 Exam Syllabus Topics:

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

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