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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 14, 2026

Q & A: 332 Questions and Answers

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About Microsoft DP-900日本語 Exam

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

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What Are the Exam Topics?

Core data concepts

This topic majorly addresses the following skills:

  • Main concepts of data analytics – data visualization, business intelligence (BI), analytics techniques (diagnostic, predictive, descriptive, cognitive, prescriptive) and basic chart types such as pie charts and bar charts are the main concepts addressed in this category. Also, data processing techniques are covered along with ETL processing.
  • Various data workloads – this involves an overview of the features of relational data as well as the description, similarities and differences between streaming data and batch data as well as.

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Free Download real DP-900日本語 practice test

The candidates for the Microsoft DP-900 test will be measured in a variety of technical skill areas. These domains are divided into several topics. It is recommended that the applicants review the exam topics in detail and choose the appropriate study materials to prepare for the test. Below are the highlights of the objectives covered in this certification exam:

  • Explain how Relational Data Works on Azure: 25-30%

    The test takers will be required to have the ability to describe some concepts in this topic, including relational data workloads and relational Azure data services. They will also need to know how to identify the basic management functions for relational data. Additionally, they need to possess a good understanding of how to use the SQL language to describe the query methods for data.

  • Explain how Non-Relational Data Works on Azure: 25-30%

    The questions from this section will evaluate the understanding of the candidates in non-relational data workloads as well as non-relational data contributions on Azure. They must be able to explain Azure File storage, Azure Cosmos DB APIs, Azure Blob Storage, and Azure Table storage. They should also be able to identify the foundational management tasks for non-relational data.

  • Explain Analytics Workloads on Azure: 25-30%

    This domain of the DP-900 exam measures one’s knowledge of analytics workloads, data processing, and ingestion on Azure, as well as the elements of modern data warehouses. The candidates will also be tested on their understanding of data visualization within Microsoft Power BI. This involves describing the specific role of dashboards, paginated reporting, interactive reports, and workflows in Power BI.

  • Explain the Concepts of Core Data: 15-20%

    Within this subject area, the students should be able to explain different categories of core data workloads that are available. To answer questions from this subtopic, the examinees should be able to explain batch data and streaming data. They should also know the attributes of relational data and core differences between streaming and batch data. It also covers their skills in core concepts of data analytics. This requires an understanding of data visualization, basic chart types, analytics techniques, data processing concepts, as well as ETL & ELT processing.

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Microsoft DP-900日本語 Exam Syllabus Topics:

SectionWeightObjectives
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 non-relational data concepts
        • 1. Use cases for non-relational data
          • 2. Characteristics of NoSQL data
            - Describe Azure storage services
            • 1. Blob Storage
              • 2. Table Storage
                • 3. File Storage
                  • 4. Queue Storage
                    Identify considerations for relational data on Azure20–25%- Describe Azure relational data services
                    • 1. Azure SQL Database
                      • 2. SQL Server on Azure Virtual Machines
                        • 3. Azure SQL Managed Instance
                          • 4. Open-source databases: PostgreSQL, MySQL, MariaDB
                            - Describe relational data concepts
                            • 1. Normalization
                              • 2. Relationships, keys, constraints
                                • 3. Query data with SQL
                                  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
                                              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 data visualization
                                                    • 1. Data models and reports
                                                      • 2. Power BI capabilities
                                                        - Describe Azure analytics services
                                                        • 1. Microsoft Fabric
                                                          • 2. Azure Databricks
                                                            • 3. Azure HDInsight
                                                              • 4. Azure Synapse Analytics
                                                                • 5. Azure Data Lake Storage Gen2
                                                                  - Describe real-time analytics
                                                                  • 1. Stream processing concepts
                                                                    • 2. Azure Stream Analytics

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