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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%)

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.

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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.

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

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For more information about the Microsoft DP-203 Exam visit the following reference link:

Microsoft DP-203 Exam Reference link

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Microsoft DP-203 Korean Exam Syllabus Topics:

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

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