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

  • Exam Code: DP-203-KR
  • Exam Name: Data Engineering on Microsoft Azure (DP-203 Korean Version)
  • Updated: Aug 12, 2026
  • Q & A: 365 Questions and Answers

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Skills measured

  • Monitor and optimize data storage and data processing (10-15%)
  • Design and develop data processing (25-30%)
  • Design and implement data security (10-15%)
  • Design and implement data storage (40-45%)

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All the details of Microsoft DP-203 Exam format?

  • Exam Duration: 130 minutes

  • Exam Format: multiple-choice

  • Exam Length: 40-60 question

  • Language: English

  • Passing score: 75%

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

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How to Register For Exam DP-203: Data Engineering on Microsoft Azure?

Exam Register Link: https://examregistration.microsoft.com/?locale=en-us&examcode=DP-203&examname=Exam%20DP-203:%20Data%20Engineering%20on%20Microsoft%20Azure&returnToLearningUrl=https%3A%2F%2Fdocs.microsoft.com%2Flearn%2Fcertifications%2Fexams%2Fdp-203

Data Engineering on Microsoft Azure Exam Certification Details:

Number of Questions40-60
Duration150 mins
Exam NameMicrosoft Certified - Azure Data Engineer Associate
Passing Score700 / 1000
Exam CodeDP-203
Books / TrainingDP-203T00: Data Engineering on Microsoft Azure
Schedule ExamPearson VUE
Exam Price$165 (USD)
Sample QuestionsData Engineering on Microsoft Azure Sample Questions

Microsoft DP-203 Korean Exam Syllabus Topics:

SectionWeightObjectives
Design and implement data security10–15%- Protect data at rest and in transit
  • 1. Implement encryption
    • 2. Configure data masking and redaction
      • 3. Manage data privacy and compliance
        - Implement authentication and authorization
        • 1. Manage access to data resources
          • 2. Configure identity and access management
            Design and develop data processing25–30%- Develop data processing solutions
            • 1. Implement incremental processing
              • 2. Implement data ingestion
                • 3. Transform data using Spark, SQL, or other tools
                  • 4. Manage data flows and dependencies
                    - Design data processing pipelines
                    • 1. Design for data integration and transformation
                      • 2. Design batch processing solutions
                        • 3. Design orchestration and scheduling
                          • 4. Design real-time processing solutions
                            Design and implement data storage40–45%- Design data storage structures
                            • 1. Design for scalability and performance
                              • 2. Design for data durability and availability
                                • 3. Design partitioning strategies
                                  • 4. Recommend storage solutions for analytical workloads
                                    - Implement data storage
                                    • 1. Create and configure data storage accounts
                                      • 2. Implement data lake storage
                                        • 3. Implement relational and non-relational data stores
                                          • 4. Manage data lifecycle and retention policies
                                            Monitor and optimize data storage and data processing10–15%- Optimize performance and cost
                                            • 1. Tune pipelines and workloads
                                              • 2. Optimize storage and compute resources
                                                • 3. Improve query and processing efficiency
                                                  - Monitor data solutions
                                                  • 1. Monitor storage performance and health
                                                    • 2. Monitor pipeline execution and errors
                                                      • 3. Log and analyze activity and usage

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