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

Microsoft DP-900日本語 test insides dumps
  • Exam Code: DP-900J
  • Exam Name: Microsoft Azure Data Fundamentals (DP-900日本語版)
  • Updated: Jul 22, 2026
  • Q & A: 320 Questions and Answers
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How to book the Microsoft DP-900: Microsoft Azure Data Fundamentals Exam

  • Step 1: Visit Microsoft Learning and search for DP-900: Microsoft Azure fundamentals.
  • Step 2: Sign up/log in to the Pearson VUE account
  • Step 3: Select a local center based on your country, date, time and confirm with a payment method.

Explain Analytics Workloads on Azure: 25-30%

  • Explain Analytics Workloads: The applicants should be able to explain transactional workloads, data warehousing workloads, and when data warehouse solutions are needed. This subtopic also covers their skills and knowledge associated with the differences between analytics and a transactional workload as well as the differences between real-time and batch.
  • Explain Modern Data Warehouse Components: The test takers should understand Azure data services for the latest data warehousing, including Azure Synapse Analytics, Azure HDInsight, Azure Data Lake, and Azure Databricks, as well as explainin the workload and architecture for modern data warehousing.
  • Explain Data Processing & Ingestion on Azure: The learners should be able to explain the fundamental practices for data loading, Azure Data Factory components, and data processing options.
  • Explain Data Visualization within Microsoft Power BI: You need to have competence in explaining the function of dashboards, interactive reports, and paginated reporting, as well as the workflow within Power BI.

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

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Microsoft DP-900日本語 Exam Syllabus Topics:

SectionWeightObjectives
Describe core data concepts25-30%- Describe ways to represent data
  • 1. Describe features of unstructured data
  • 2. Describe features of semi-structured data
  • 3. Describe features of structured data
- Identify options for data storage
  • 1. Describe types of databases
  • 2. Describe common formats for data files
Describe an analytics workload on Azure25-30%- Describe analytics concepts
  • 1. Describe analytical workloads
  • 2. Describe ETL and ELT processes
  • 3. Describe transactional workloads
  • 4. Describe data warehousing
- Describe data visualization in Microsoft Power BI
  • 1. Describe Power BI
  • 2. Describe Power BI reports and dashboards
  • 3. Describe Power BI tools and workflow
- Describe Azure data analytics services
  • 1. Describe Azure HDInsight
  • 2. Describe Azure Stream Analytics
  • 3. Describe Azure Databricks
  • 4. Describe Azure Synapse Analytics
  • 5. Describe Azure Data Factory
  • 6. Describe Microsoft Fabric
Identify considerations for relational data on Azure20-25%- Describe relational concepts
  • 1. Describe normalization
  • 2. Identify features of relational data
- Describe relational Azure data services
  • 1. Describe Azure Database for MySQL
  • 2. Describe SQL Server on Azure Virtual Machines
  • 3. Describe Azure SQL Managed Instance
  • 4. Describe Azure SQL Database
  • 5. Describe Azure Database for PostgreSQL
  • 6. Describe Azure SQL family of products
  • 7. Describe Azure Database for MariaDB
Describe considerations for working with non-relational data on Azure15-20%- Describe non-relational Azure data services
  • 1. Describe Azure File storage
  • 2. Describe Azure Blob storage
  • 3. Describe Azure Cosmos DB
  • 4. Describe Azure Table storage
- Describe non-relational concepts
  • 1. Describe non-relational data offerings
  • 2. Identify non-relational data

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