Microsoft DP-900日本語 Q&A - in .pdf

  • DP-900日本語 pdf
  • Exam Code: DP-900日本語
  • Exam Name: Microsoft Azure Data Fundamentals (DP-900日本語版)
  • Updated: Sep 28, 2026
  • Q & A: 332 Questions and Answers
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  • Q & A: 332 Questions and Answers
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  • DP-900日本語 Testing Engine
  • Exam Code: DP-900日本語
  • Exam Name: Microsoft Azure Data Fundamentals (DP-900日本語版)
  • Updated: Sep 28, 2026
  • Q & A: 332 Questions and Answers
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General Overview of Microsoft DP-900 Exam

The Microsoft DP-900 exam evaluates the individuals’ understanding of core data concepts, analytics workloads on Azure, as well as how to function with relational and non-relational data within Azure. The test contains 40-60 questions and the applicants have 90 minutes for the completion. The students or instructors who want to take this exam are required to schedule it through Certiport while the non-students are to schedule the test with Pearson VUE. The fee for the exam is $99 and it is available in a range of languages, including English, Spanish, French, Korean, German, Japanese, and Simplified Chinese.

The Microsoft DP-900 exam is intended for candidates who already have foundational knowledge and skills in performing basic tasks and using Microsoft Azure data services. It is also recommended for those who are starting their careers in the field of cloud data. Although there are no strict prerequisites, every individual who desires to take DP-900 test should have familiarity with non-relational and relational data as well as various types of data workloads such as analytical and transactional.

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

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Skills measured

  • Describe core data concepts (15-20%)
  • Describe how to work with relational data on Azure (25-30%)
  • Describe an analytics workload on Azure (25-30%)
  • Describe how to work with non-relational data on Azure (25-30%)

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Explain the Techniques Involved in Working with Non-Relational Data on Microsoft Azure: 25-30%

  • Explain Offerings of Non-Relational Data on Azure: The individuals need to have competence in explaining Azure Table storage, Azure File storage, Azure data service for non-relational workloads, Azure Blob Storage, and Azure Cosmos DB APIs.
  • Identify the Fundamental Management Functions for Non-Relational Data: The examinees should have competence in explaining deployment and provisioning of non-relational data and the techniques for deployment. They also need the skills in identifying the components of data security, fundamental connectivity issues, and non-relational data management tools.
  • Explain Non-Relational Data Workloads: The candidates should be able to explain the attributes of non-relational data and types of NoSQL and non-relational data. They need to have expertise in recommending the appropriate data stores and establishing them to utilize non-relational data.

Microsoft DP-900日本語 Exam Syllabus Topics:

SectionWeightObjectives
Describe core data concepts25–30%- 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
        - Describe data workloads
        • 1. Batch and streaming data
          • 2. Analytical workloads
            • 3. Transactional workloads
              Describe an analytics workload on Azure25–30%- Describe data visualization
              • 1. Power BI capabilities
                • 2. Data models and reports
                  - Describe Azure analytics services
                  • 1. Azure Databricks
                    • 2. Azure HDInsight
                      • 3. Microsoft Fabric
                        • 4. Azure Data Lake Storage Gen2
                          • 5. Azure Synapse Analytics
                            - Describe real-time analytics
                            • 1. Stream processing concepts
                              • 2. Azure Stream Analytics
                                - Describe big data and analytics concepts
                                • 1. Data ingestion and processing
                                  • 2. Data lakes and data warehouses
                                    • 3. Modern data warehouse architecture
                                      Identify considerations for relational data on Azure20–25%- Describe relational data concepts
                                      • 1. Query data with SQL
                                        • 2. Relationships, keys, constraints
                                          • 3. Normalization
                                            - Describe Azure relational data services
                                            • 1. Open-source databases: PostgreSQL, MySQL, MariaDB
                                              • 2. SQL Server on Azure Virtual Machines
                                                • 3. Azure SQL Database
                                                  • 4. Azure SQL Managed Instance
                                                    Describe considerations for working with non-relational data on Azure15–20%- Describe Azure Cosmos DB
                                                    • 1. Capabilities and features
                                                      • 2. Consistency levels and partitioning
                                                        • 3. APIs and data models
                                                          - Describe non-relational data concepts
                                                          • 1. Use cases for non-relational data
                                                            • 2. Characteristics of NoSQL data
                                                              - Describe Azure storage services
                                                              • 1. File Storage
                                                                • 2. Queue Storage
                                                                  • 3. Blob Storage
                                                                    • 4. Table Storage
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