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

DP-900日本語 real exams

Exam Code: DP-900J

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

Updated: Sep 03, 2026

Q & A: 332 Questions and Answers

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Certification Paths Available

Upon earning Microsoft Certified: Azure Data Fundamentals, you will be able to advance your career to higher-level certifications. For instance, it can be a starting point for Microsoft Certified: Azure Data Engineer Associate or Microsoft Certified: Azure Database Administrator Associate. However, this fundamental accreditation is not a requirement for earning any of the next certificates. Therefore, all you have to do is to pass Microsoft DP-900 exam and prepare to face the real-world challenges as you advance in your career.

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

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How to operate with non-relational data on Azure

The main concepts covered in this domain include:

  • Non relation data workloads – this sub-section mostly emphasizes the features of non-relational data, when to use it, one's knowledge of the variants of NoSQL and non-relational data, and the ability to choose and recommend appropriate data store.
  • Offerings non-relational data on Azure – within this topic, the learner will be conversant with the following in Azure: data services, Cosmos DB APIs, Table storage, Blob storage, File storage.
  • Core administration tasks – this sub-domain covers the processes of deployment and provisioning when it comes to non-relational data, data security, diverse tools for management, and defining the issues with connectivity.

Microsoft DP-900日本語 Exam Syllabus Topics:

SectionWeightObjectives
Describe core data concepts25–30%- Describe data workloads
  • 1. Batch and streaming data
    • 2. Analytical workloads
      • 3. Transactional workloads
        - 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
              Identify considerations for relational data on Azure20–25%- Describe relational data concepts
              • 1. Query data with SQL
                • 2. Normalization
                  • 3. Relationships, keys, constraints
                    - Describe Azure relational data services
                    • 1. SQL Server on Azure Virtual Machines
                      • 2. Azure SQL Managed Instance
                        • 3. Open-source databases: PostgreSQL, MySQL, MariaDB
                          • 4. Azure SQL Database
                            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 Databricks
                                  • 2. Azure HDInsight
                                    • 3. Microsoft Fabric
                                      • 4. Azure Synapse Analytics
                                        • 5. Azure Data Lake Storage Gen2
                                          - Describe data visualization
                                          • 1. Power BI capabilities
                                            • 2. Data models and reports
                                              - Describe big data and analytics concepts
                                              • 1. Data lakes and data warehouses
                                                • 2. Data ingestion and processing
                                                  • 3. Modern data warehouse architecture
                                                    Describe considerations for working with non-relational data on Azure15–20%- Describe Azure Cosmos DB
                                                    • 1. APIs and data models
                                                      • 2. Capabilities and features
                                                        • 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. Table Storage
                                                                • 2. Blob Storage
                                                                  • 3. File Storage
                                                                    • 4. Queue Storage

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