Microsoft DP-900-KR exam dumps : Microsoft Azure Data Fundamentals (DP-900 Korean Version)

  • Exam Code: DP-900-KR
  • Exam Name: Microsoft Azure Data Fundamentals (DP-900 Korean Version)
  • Updated: Aug 30, 2026     Q & A: 332 Questions and Answers

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About Microsoft DP-900 Korean Exam

Helpful Training Course for Acing DP-900

To help students get fully ready for DP-900, Microsoft has created an official 1-day teacher-guided program for students named ‘Course DP-900T00-A: Microsoft Azure Data Fundamentals’. There are 4 modules in this course which will address all the topics needed for the Microsoft DP-900. However, such a class does not have any related lab exercises, meaning students will not get the scope for applying the things they have learnt in theory. In general, this training is perfect for those who want to learn the main concepts and skills needed to provide cloud data services with the help of Microsoft Azure.

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

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Introduction to Microsoft DP-900: Microsoft Azure Data Fundamentals Exam

Microsoft Azure Data Fundamentals is an exam that identifies individuals who have the knowledge to work with Azure data storage features. Building on previous core principles of data management, Azure Data Fundamentals exam is designed to evaluate the ability of the candidate. Money designed to assess the skills level for both professionals and students. Determine the type of skills required for a particular situation, for example, a cloud administrator or a data analyst. Gen candidate will have to know the fundamentals of Data Management to work with Azure data storage, create tools to manage data, locate, protect and process it. Relevant topics in a data management environment, a certified candidate should understand. Dml, Db, protection tools through recovery, recovery strategies, documentation data management policies, data loss prevention tools to backup and recovery for backup recovery.

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Explain the Techniques Involved in Working with Non-Relational Data on Microsoft Azure: 25-30%

  • 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.
  • 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 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.

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Microsoft DP-900 Korean Exam Syllabus Topics:

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

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