Microsoft DP-203 Korean : Data Engineering on Microsoft Azure (DP-203 Korean Version)

  • Exam Code: DP-203 Korean
  • Exam Name: Data Engineering on Microsoft Azure (DP-203 Korean Version)
  • Updated: Aug 02, 2026     Q & A: 365 Questions and Answers

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Certification Topics of Microsoft DP-203 Exam

  • Monitor and optimize data storage and data processing (10-15%)

  • Design and implement data security (10-15%)

  • Design and implement data storage (40-45%)

  • Design and develop data processing (25-30%)

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Following are some reference material for actual Microsoft DP-203 Korean exam test

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Languages: English, Chinese (Simplified), Japanese, Korean

Retirement date: none

This exam measures your ability to accomplish the following technical tasks: design and implement data storage; design and develop data processing; design and implement data security; and monitor and optimize data storage and data processing.

Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/dp-203

Microsoft DP-203 Korean Exam Syllabus Topics:

SectionWeightObjectives
Design and implement data storage25-30%- Design data storage structures
  • 1. Recommend appropriate storage accounts and services
    • 2. Design a data serialization format strategy
      • 3. Design a data partitioning strategy
        - Develop data storage solutions
        • 1. Implement Azure Data Lake Storage solutions
          • 2. Implement Azure Blob Storage solutions
            • 3. Implement relational data stores (Azure SQL, Synapse)
              Secure data solutions- Implement data security
              • 1. Implement encryption at rest and in transit
                • 2. Manage access control with Azure RBAC
                  - Ensure compliance
                  • 1. Use Microsoft Purview for governance
                    Monitor and optimize data solutions30-35%- Monitor data processing
                    • 1. Troubleshoot data workflows
                      • 2. Monitor pipelines using Azure Monitor
                        - Optimize performance
                        • 1. Optimize query performance in Synapse
                          • 2. Optimize data storage performance
                            Develop data processing40-45%- Ingest and transform data
                            • 1. Implement stream processing solutions
                              • 2. Implement batch processing solutions
                                • 3. Use Azure Data Factory for pipelines
                                  - Develop data transformation logic
                                  • 1. Use Spark in Azure Databricks
                                    • 2. Use SQL-based transformations

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