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

Microsoft DP-203 Deutsch Exam Syllabus Topics:

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

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