Microsoft DP-900J exam dumps : 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: Aug 05, 2026     Q & A: 320 Questions and Answers

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Workload analytics on Azure

  • Date processing and ingestion on Azure – main topics within this subdomain include data loading common practices, Azure Data Factory components (activities, pipeline, etc.), and data processing.
  • Data visualization in Microsoft Power BI – this topic requires candidates to learn more about paginated reporting, dashboards, interactive reports, as well as workflow in Power BI.
  • Analytics workloads – under this topic, candidates should learn more about transactional workloads as well as data warehousing workloads. Also, they have to get skilled in differentiating between an analytics and a transactional workload, know the difference between real and batch time, and be able to determining when a data warehouse solution is required.
  • Elements of a modern data warehouse – this sub-section is focused on Azure data services related to modern data warehousing. In addition, applicants should be familiar with modern data warehousing workload and architecture.

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

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General Overview of Microsoft DP-900 Exam

The Microsoft DP-900 exam evaluates the individuals’ understanding of core data concepts, analytics workloads on Azure, as well as how to function with relational and non-relational data within Azure. The test contains 40-60 questions and the applicants have 90 minutes for the completion. The students or instructors who want to take this exam are required to schedule it through Certiport while the non-students are to schedule the test with Pearson VUE. The fee for the exam is $99 and it is available in a range of languages, including English, Spanish, French, Korean, German, Japanese, and Simplified Chinese.

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Microsoft DP-900日本語 Exam Syllabus Topics:

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

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