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  • Exam Code: DP-900J
  • Exam Name: Microsoft Azure Data Fundamentals (DP-900日本語版)
  • Last Updated: Aug 15, 2026
  • Q & A: 332 Questions and Answers
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  • Exam Code: DP-900J
  • Exam Name: Microsoft Azure Data Fundamentals (DP-900日本語版)
  • Last Updated: Aug 15, 2026
  • Q & A: 332 Questions and Answers
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About Microsoft Azure Data Fundamentals (DP-900日本語版) : DP-900日本語 still valid exam

The Microsoft Azure Data Fundamentals (DP-900日本語版) certification exam also covers the various tools and services available in Azure for data management, such as Azure Data Factory, Azure Databricks, and Azure Synapse Analytics. Candidates are expected to have a solid understanding of these tools and services, including their features, functions, and benefits. Overall, the DP-900 certification exam is a great way for individuals to gain a fundamental understanding of data management in the Azure cloud environment and validate their skills and knowledge in this area.

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Microsoft DP-900 Exam is a great starting point for anyone who is new to Azure data services. DP-900J exam covers a wide range of topics, including Azure SQL Database, Azure Cosmos DB, Azure Data Lake Storage, and Azure Synapse Analytics. DP-900J exam also covers concepts such as data ingestion, data transformation, and data visualization. This makes it an ideal certification for anyone who is looking to start a career in data management or data analytics.

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Microsoft DP-900 or Azure Data Fundamentals Exam is an excellent certification exam for individuals who are interested in gaining foundational knowledge of data services on Azure. Microsoft Azure Data Fundamentals (DP-900日本語版) certification will not only help you to start your career in data and analytics but will also provide you with a strong foundation for advanced certifications in the future.

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

Microsoft DP-900日本語 Exam Syllabus Topics:

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

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