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

DP-900 Korean real exams

Exam Code: DP-900-KR

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

Updated: Aug 20, 2026

Q & A: 332 Questions and Answers

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Exam DP-900: Microsoft Azure Data Fundamentals

Candidates for this exam should have foundational knowledge of core data concepts and how they are implemented using Microsoft Azure data services.

This exam is intended for candidates beginning to work with data in the cloud.

Candidates should be familiar with the concepts of relational and non-relational data, and different types of data workloads such as transactional or analytical.

Azure Data Fundamentals can be used to prepare for other Azure role-based certifications like Azure Database Administrator Associate or Azure Data Engineer Associate, but it’s not a prerequisite for any of them.

Part of the requirements for: Microsoft Certified: Azure Data Fundamentals

Download exam skills outline

How to operate with non-relational data on Azure

The main concepts covered in this domain include:

  • Offerings non-relational data on Azure – within this topic, the learner will be conversant with the following in Azure: data services, Cosmos DB APIs, Table storage, Blob storage, File storage.
  • Non relation data workloads – this sub-section mostly emphasizes the features of non-relational data, when to use it, one's knowledge of the variants of NoSQL and non-relational data, and the ability to choose and recommend appropriate data store.
  • Core administration tasks – this sub-domain covers the processes of deployment and provisioning when it comes to non-relational data, data security, diverse tools for management, and defining the issues with connectivity.

What requirements should you fulfill before taking the Microsoft DP-900 exam?

The candidates for this certification exam are those individuals who want to validate their foundational-level experience in working with data within Cloud. They should possess the basic knowledge and skills in the domain of core data concepts. They also need to have an understanding of how these are implemented with the use of Microsoft Azure data services.

The applicants do not have to fulfill any requirements to take the Microsoft DP-900 test or get the associated certification. However, they must be familiar with different concepts of non-relational and relational data. They should also know various types of data workloads that are available, including analytical and transactional. Additionally, the students must develop mastery of the exam topics before sitting for this test.

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

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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.
  • 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.
  • 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.

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Microsoft DP-900 Korean Exam Syllabus Topics:

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