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Microsoft DP-900日本語 real answers - 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: Sep 23, 2026
  • Q & A: 332 Questions and Answers
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About Microsoft DP-900日本語 Exam

For more info read reference:

Microsoft learning site Administer infrastructure resources in Azure Azure Storage Azure Network

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

Career Potential with Microsoft DP-900 Exam

The Microsoft Certified: Azure Data Fundamentals certification is a foundational certificate but the candidates can still get a lucrative job holding it. Some of the positions that the certified professionals can consider include an IT Administrator, a Systems Administrator, a Junior Data Analyst, a Program Manager, and an Azure Security Engineer. The salary potential for these job roles is an average of $57,630 per annum.

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Microsoft DP-900 Practice Test Questions, Microsoft DP-900 Exam Practice Test Questions

The Microsoft DP-900 exam is a qualifying test for obtaining the Microsoft Certified: Azure Data Fundamentals certification. This exam is intended for the entry-level professionals looking to take up a career path in the IT field. Although it is not a requirement for any advanced-level certificate, the DP-900: Microsoft Azure Data Fundamentals test is a great foundation to prepare the individuals for other Azure role-based options. Thus, the certified candidates can pursue two certifications: Azure Data Engineer Associate or Azure Database Administrator Associate.

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  • Systems Administrator – as a sysadmin, you will be tasked with providing hands-on support when it comes to system maintenance, operation and administration. You will also be the person concerned in making recommendation of an appropriate software to be deployed. The average salary is estimated to be $63k.
  • Cloud Solutions Analyst – an early career as cloud solutions analyst or architect is quite lucrative. You can earn up to an average salary of $80k annually with even less than 1 year of working experience in this role. Once you develop in this job, the salary may rise up to the average of $126k per annum. Although the role is so much demanding, you should be ready to do proper evaluation and performance testing of a cloud solution before integration. The main task of these specialists is to ensure that the performance of the system is optimized.
  • Systems Engineer – this role will keep you engaged in the design and the development of the cloud solutions that are appropriate to the business at hand. These professionals also analyze both the system and software requirements before giving design guidelines. This role is estimated to earn you an average salary of $81k per annum, as per PayScale.

Microsoft DP-900日本語 Exam Syllabus Topics:

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

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