Microsoft DP-900日本語 Valid Dump : 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 08, 2026

Q & A: 332 Questions and Answers

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

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.

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How to Register For Exam DP-900: Microsoft Azure Data Fundamentals?

Exam Register Link: https://examregistration.microsoft.com/?locale=en-us&examcode=DP-900&examname=Exam%20DP-900:%20Microsoft%20Azure%20Data%20Fundamentals&returnToLearningUrl=https%3A%2F%2Fdocs.microsoft.com%2Flearn%2Fcertifications%2Fexams%2Fdp-900

Microsoft DP-900日本語 Exam Syllabus Topics:

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