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Familiarize yourself with the format of the Microsoft DP-203 Exam

Microsoft Data Platform (DP) is an exam for IT professionals who are responsible for designing and implementing data processing solutions that integrate with Microsoft platforms, applications, and services. Candidates prepare for this exam by taking the Microsoft Official Curriculum (MOC) course for the Azure Data Engineering on Microsoft Azure certification. The DP-203 exam tests your ability to design and implement data processing solutions on Azure in a cloud environment. You need to understand how to design and create data services with Azure Data Factory; how to create, manage and deploy data models using the Azure Data Catalog; and how to manage the lifecycle of a data solution using Azure Data Lake Analytics. Microsoft DP-203 Dumps Questions and Answers are prepared by experts and reviewed and approved by Microsoft. The test is based on the latest version of Microsoft Data Platform that includes SQL Server 2016, SQL Database, HDInsight, and Power BI. The questions test both technical skills and business knowledge so you need to have a good understanding of both areas in order to pass the test.

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

Certification Topics of Microsoft DP-203 Exam

  • Design and develop data processing (25-30%)

  • Design and implement data security (10-15%)

  • Monitor and optimize data storage and data processing (10-15%)

  • Design and implement data storage (40-45%)

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Microsoft DP-203 Exam Syllabus Topics:

SectionWeightObjectives
Design and implement data storage40–45%- 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
          - Implement data storage
          • 1. Implement relational and non-relational data stores
            • 2. Implement data lake storage
              • 3. Create and configure data storage accounts
                • 4. Manage data lifecycle and retention policies
                  Monitor and optimize data storage and data processing10–15%- Optimize performance and cost
                  • 1. Improve query and processing efficiency
                    • 2. Tune pipelines and workloads
                      • 3. Optimize storage and compute resources
                        - 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. Configure data masking and redaction
                                • 2. Manage data privacy and compliance
                                  • 3. Implement encryption
                                    - 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. Manage data flows and dependencies
                                          • 2. Implement data ingestion
                                            • 3. Implement incremental processing
                                              • 4. Transform data using Spark, SQL, or other tools
                                                - Design data processing pipelines
                                                • 1. Design batch processing solutions
                                                  • 2. Design orchestration and scheduling
                                                    • 3. Design for data integration and transformation
                                                      • 4. Design real-time processing solutions

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