DP-900日本語 Q&A - in .pdf

  • DP-900日本語 pdf
  • Exam Code: DP-900日本語
  • Exam Name: Microsoft Azure Data Fundamentals (DP-900日本語版)
  • Updated: Sep 28, 2026
  • Q & A: 332 Questions and Answers
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  • Updated: Sep 28, 2026
  • Q & A: 332 Questions and Answers
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  • Exam Code: DP-900日本語
  • Exam Name: Microsoft Azure Data Fundamentals (DP-900日本語版)
  • Updated: Sep 28, 2026
  • Q & A: 332 Questions and Answers
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Workload analytics on Azure

  • 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.
  • 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.
  • 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.

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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

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

How to operate with relational data on Azure

Here, the candidate should be equipped with knowledge and skills in the following sub domains:

  • Relational data workloads – the candidate has to gain skills in identifying the appropriate data offerings when it comes to relational workload and learn more about structures of relational data.
  • Data querying techniques that require utilizing SQL language – it deals with the Data Manipulation Language (DML) and Data Definition Language (DDL) as well as querying relational data on Azure SQL DB.
  • Relational Azure data services – this section of the exam is focused on the following: the understanding of IaaS, SaaS and PaaS solutions and their comparison, Azure SQL DB services such as Azure SQL managed instance and Azure virtual machine, Azure Synapse Analytics, and Azure Database for MariaDB, PostgreSQL and for MySQL.
  • Identification of basic management roles for relational data – under this sub domain there are several skills covered that include the deployment and provisioning of relational data, various deployment methods such as Azure Resource Manager templates, Azure portal, Azure command-line interface (CLI), etc. Also, one should be knowledgeable in data components identification (authentication and firewall), the identification of basic connectivity problems such as accessing Azure VNets, firewalls, access from the internet and authentication). One more knowledge area involved is query tools (SQL Management Studio, Azure Data Studio, utility, sqlcmd etc.).

Microsoft DP-900日本語 Exam Syllabus Topics:

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

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