Microsoft DP-900 Korean exam - in .pdf

DP-900 Korean pdf
  • Exam Code: DP-900 Korean
  • Exam Name: Microsoft Azure Data Fundamentals (DP-900 Korean Version)
  • Updated: Sep 23, 2026
  • Q & A: 332 Questions and Answers
  • PDF Price: $69.99
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  • Exam Code: DP-900 Korean
  • Exam Name: Microsoft Azure Data Fundamentals (DP-900 Korean Version)
  • Updated: Sep 23, 2026
  • Q & A: 332 Questions and Answers
  • PDF Version + PC Test Engine + Online Test Engine
  • Value Pack Total: $139.98  $89.99
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Microsoft DP-900 Korean exam - Testing Engine

DP-900 Korean Testing Engine
  • Exam Code: DP-900 Korean
  • Exam Name: Microsoft Azure Data Fundamentals (DP-900 Korean Version)
  • Updated: Sep 23, 2026
  • Q & A: 332 Questions and Answers
  • Software Price: $69.99
  • Testing Engine

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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 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 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 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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The Microsoft Certified: Azure Data Fundamentals certification is a foundational certificate but the candidates can still get a lucrative job holding it. Some of the positions that the certified professionals can consider include an IT Administrator, a Systems Administrator, a Junior Data Analyst, a Program Manager, and an Azure Security Engineer. The salary potential for these job roles is an average of $57,630 per annum.

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

Microsoft DP-900 Korean Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Describe considerations for working with non-relational data on Azure15–20%- Describe Azure storage services
  • 1. File Storage
    • 2. Blob Storage
      • 3. Table Storage
        • 4. Queue Storage
          - Describe non-relational data concepts
          • 1. Characteristics of NoSQL data
            • 2. Use cases for non-relational data
              - Describe Azure Cosmos DB
              • 1. Capabilities and features
                • 2. APIs and data models
                  • 3. Consistency levels and partitioning
                    Topic 2: Identify considerations for relational data on Azure20–25%- Describe relational data concepts
                    • 1. Normalization
                      • 2. Query data with SQL
                        • 3. Relationships, keys, constraints
                          - Describe Azure relational data services
                          • 1. Azure SQL Database
                            • 2. SQL Server on Azure Virtual Machines
                              • 3. Open-source databases: PostgreSQL, MySQL, MariaDB
                                • 4. Azure SQL Managed Instance
                                  Topic 3: Describe core data concepts25–30%- Describe data workloads
                                  • 1. Batch and streaming data
                                    • 2. Transactional workloads
                                      • 3. Analytical workloads
                                        - Describe types of data
                                        • 1. Structured, semi-structured, and unstructured data
                                          • 2. File formats
                                            - Describe roles and responsibilities
                                            • 1. Data engineer, data analyst, database administrator
                                              Topic 4: Describe an analytics workload on Azure25–30%- Describe real-time analytics
                                              • 1. Azure Stream Analytics
                                                • 2. Stream processing concepts
                                                  - Describe big data and analytics concepts
                                                  • 1. Modern data warehouse architecture
                                                    • 2. Data lakes and data warehouses
                                                      • 3. Data ingestion and processing
                                                        - Describe data visualization
                                                        • 1. Power BI capabilities
                                                          • 2. Data models and reports
                                                            - Describe Azure analytics services
                                                            • 1. Azure HDInsight
                                                              • 2. Azure Synapse Analytics
                                                                • 3. Azure Data Lake Storage Gen2
                                                                  • 4. Azure Databricks
                                                                    • 5. Microsoft Fabric

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