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

Microsoft DP-203日本語 Exam Syllabus Topics:

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

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