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

Exam Code: DP-900J

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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How to operate with relational data on Azure

Here, the candidate should be equipped with knowledge and skills in the following sub domains:

  • Relational data workloads – the candidate has to gain skills in identifying the appropriate data offerings when it comes to relational workload and learn more about structures of relational data.
  • Data querying techniques that require utilizing SQL language – it deals with the Data Manipulation Language (DML) and Data Definition Language (DDL) as well as querying relational data on Azure SQL DB.
  • Relational Azure data services – this section of the exam is focused on the following: the understanding of IaaS, SaaS and PaaS solutions and their comparison, Azure SQL DB services such as Azure SQL managed instance and Azure virtual machine, Azure Synapse Analytics, and Azure Database for MariaDB, PostgreSQL and for MySQL.
  • Identification of basic management roles for relational data – under this sub domain there are several skills covered that include the deployment and provisioning of relational data, various deployment methods such as Azure Resource Manager templates, Azure portal, Azure command-line interface (CLI), etc. Also, one should be knowledgeable in data components identification (authentication and firewall), the identification of basic connectivity problems such as accessing Azure VNets, firewalls, access from the internet and authentication). One more knowledge area involved is query tools (SQL Management Studio, Azure Data Studio, utility, sqlcmd etc.).

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

  • Explain the Concepts of Relational Data Workloads: The examinees should be able to explain the structures of relational data and identify the appropriate data for relational workloads.
  • Explain Relational Azure Data Services: The individuals should have the ability to explain and compare SaaS, PaaS, and IaaS solutions as well as Azure Synapse Analytics. They also need the knowledge of Azure SQL database services, Azure Database for PostgreSQL, Azure Database for MySQL, and Azure Database for MariaDB.
  • Identify the Fundamental Management Tasks for Relational Data: The applicants should be able to explain the deployment and provisioning of relational data services. They also need to understand the techniques for deployment, such as Azure Resource Manager templates, Azure portal, Azure CLI, and Azure PowerShell. In addition, the students should be able to identify the fundamental connectivity issues and components of data security.
  • Explain the Query Methods for Data with the SQL Language: The learners should be capable of comparing the Data Manipulation Language with the Data Definition Language. They should also be able to query relational data within Azure Database for MySQL, Azure SQL Database, and Azure Database for PostgreSQL.

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

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