Microsoft DP-900 Korean Exam : Microsoft Azure Data Fundamentals (DP-900 Korean Version)

DP-900 Korean
  • Exam Code: DP-900-KR
  • Exam Name: Microsoft Azure Data Fundamentals (DP-900 Korean Version)
  • Updated: Aug 08, 2026
  • Q & A: 320 Questions and Answers

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About Microsoft DP-900 Korean Exam

Topics of Microsoft DP-900: Microsoft Azure Data Fundamentals Exam

  • Describe how to work with relational data on Azure (25-30%)
  • Describe how to work with non-relational data on Azure (25-30%)
  • Describe an analytics workload on Azure (25-30%)
  • Describe core data concepts (15-20%)

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The candidates for the Microsoft DP-900 test will be measured in a variety of technical skill areas. These domains are divided into several topics. It is recommended that the applicants review the exam topics in detail and choose the appropriate study materials to prepare for the test. Below are the highlights of the objectives covered in this certification exam:

  • Explain the Concepts of Core Data: 15-20%

    Within this subject area, the students should be able to explain different categories of core data workloads that are available. To answer questions from this subtopic, the examinees should be able to explain batch data and streaming data. They should also know the attributes of relational data and core differences between streaming and batch data. It also covers their skills in core concepts of data analytics. This requires an understanding of data visualization, basic chart types, analytics techniques, data processing concepts, as well as ETL & ELT processing.

  • Explain how Non-Relational Data Works on Azure: 25-30%

    The questions from this section will evaluate the understanding of the candidates in non-relational data workloads as well as non-relational data contributions on Azure. They must be able to explain Azure File storage, Azure Cosmos DB APIs, Azure Blob Storage, and Azure Table storage. They should also be able to identify the foundational management tasks for non-relational data.

  • Explain how Relational Data Works on Azure: 25-30%

    The test takers will be required to have the ability to describe some concepts in this topic, including relational data workloads and relational Azure data services. They will also need to know how to identify the basic management functions for relational data. Additionally, they need to possess a good understanding of how to use the SQL language to describe the query methods for data.

  • Explain Analytics Workloads on Azure: 25-30%

    This domain of the DP-900 exam measures one’s knowledge of analytics workloads, data processing, and ingestion on Azure, as well as the elements of modern data warehouses. The candidates will also be tested on their understanding of data visualization within Microsoft Power BI. This involves describing the specific role of dashboards, paginated reporting, interactive reports, and workflows in Power BI.

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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.

Microsoft DP-900 Korean Exam Syllabus Topics:

TopicDetails
Topic 1
  • Describe considerations for working with non-relational data on Azure: Aspiring Microsoft data engineers gain insight into Azure's non-relational data capabilities in this topic. It discusses Azure Storage options, including Blob, Table, and Queue Storage, suitable for diverse scenarios. Additionally, the features and strengths of Azure Cosmos DB, such as global distribution and multi-model support, are outlined.
Topic 2
  • Describe an analytics workload: This topic introduces aspiring Microsoft data engineers to the components of large-scale analytics, such as data ingestion, transformation, and querying. It also discusses real-time data analytics considerations, including low-latency processing with Azure Stream Analytics. Finally, data visualization with Microsoft Power BI, focusing on interactive dashboards and reports, is covered.
Topic 3
  • Identify considerations for relational data on Azure: This topic provides aspiring Microsoft data engineers with a clear understanding of relational data concepts, including schemas, tables, keys, and normalization. It further explores relational Azure data services such as Azure SQL Database and Azure Database for MySQL, highlighting their use cases and capabilities.
Topic 4
  • Describe core data concepts: In this topic, aspiring Microsoft data engineers explore fundamental ways to represent data, such as structured, semi-structured, and unstructured formats. Additionally, the topic explains various data storage options, emphasizing file, database, and object storage. It also details common data workloads, including transactional, analytical, and streaming workloads. Lastly, the roles and responsibilities for managing data workloads, such as administrators, engineers, and analysts, are clarified.

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

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