Microsoft Data Engineering on Microsoft Azure : DP-203

DP-203 real exams

Exam Code: DP-203

Exam Name: Data Engineering on Microsoft Azure

Updated: Sep 28, 2026

Q & A: 365 Questions and Answers

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Data Engineering on Microsoft Azure Exam Certification Details:

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

What is the salary of a Microsoft DP-203 certified professional?

The Average salary of different countries of Microsoft DP-203 Certified professional

  • UK - 78707 Pounds

  • United States - $104,000 USD

  • India - 7905404 INR

All the details of Microsoft DP-203 Exam format?

  • Exam Length: 40-60 question

  • Language: English

  • Exam Duration: 130 minutes

  • Exam Format: multiple-choice

  • Passing score: 75%

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

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Microsoft DP-203 Exam Syllabus Topics:

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

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