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

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Certification Topics of Microsoft DP-203 Exam

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

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

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

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

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

Exam DP-203: Data Engineering on Microsoft Azure

Candidates for this exam should have subject matter expertise integrating, transforming, and consolidating data from various structured and unstructured data systems into a structure that is suitable for building analytics solutions.

Azure Data Engineers help stakeholders understand the data through exploration, and they build and maintain secure and compliant data processing pipelines by using different tools and techniques. These professionals use various Azure data services and languages to store and produce cleansed and enhanced datasets for analysis.

Azure Data Engineers also help ensure that data pipelines and data stores are high-performing, efficient, organized, and reliable, given a set of business requirements and constraints. They deal with unanticipated issues swiftly, and they minimize data loss. They also design, implement, monitor, and optimize data platforms to meet the data pipelines needs.

A candidate for this exam must have strong knowledge of data processing languages such as SQL, Python, or Scala, and they need to understand parallel processing and data architecture patterns.

Part of the requirements for: Microsoft Certified: Azure Data Engineer Associate

Download exam skills outline

Microsoft DP-203 Deutsch Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Monitor and optimize data solutions30-35%- Monitor data processing
  • 1. Troubleshoot data workflows
    • 2. Monitor pipelines using Azure Monitor
      - Optimize performance
      • 1. Optimize data storage performance
        • 2. Optimize query performance in Synapse
          Topic 2: Secure data solutions- Ensure compliance
          • 1. Use Microsoft Purview for governance
            - Implement data security
            • 1. Manage access control with Azure RBAC
              • 2. Implement encryption at rest and in transit
                Topic 3: Develop data processing40-45%- Ingest and transform data
                • 1. Implement batch processing solutions
                  • 2. Use Azure Data Factory for pipelines
                    • 3. Implement stream processing solutions
                      - Develop data transformation logic
                      • 1. Use SQL-based transformations
                        • 2. Use Spark in Azure Databricks
                          Topic 4: Design and implement data storage25-30%- Develop data storage solutions
                          • 1. Implement Azure Data Lake Storage solutions
                            • 2. Implement Azure Blob Storage solutions
                              • 3. Implement relational data stores (Azure SQL, Synapse)
                                - Design data storage structures
                                • 1. Recommend appropriate storage accounts and services
                                  • 2. Design a data partitioning strategy
                                    • 3. Design a data serialization format strategy

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