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All the details of Microsoft DP-203 Exam format?

  • Exam Duration: 130 minutes

  • Passing score: 75%

  • Language: English

  • Exam Format: multiple-choice

  • Exam Length: 40-60 question

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

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What should I know before taking the Microsoft DP-203 exam?

Microsoft offers Data Engineering on Microsoft Azure certification to those who wish to demonstrate their knowledge of data engineering on the Microsoft Cloud. The exam comprises multiple-choice questions, and each question is worth one mark. The candidates are required to attempt 60 questions in total, i.e., within 130 minutes. In order to take this exam, the candidates are required to have knowledge of the fundamental concepts related to the subject matter. Knowledge of basic cloud computing concepts (such as virtual machines, virtual networks, etc.) would be beneficial for the candidates. Microsoft DP-203 exam dumps contains an online study guide that explains all the concepts and answers to practice questions. Candidates should try to understand the concepts completely to gain good marks on the test.

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Microsoft DP-203 Deutsch Exam Syllabus Topics:

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

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