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All the details of Microsoft DP-203 Exam format?

  • Language: English

  • Exam Length: 40-60 question

  • Exam Duration: 130 minutes

  • Passing score: 75%

  • Exam Format: multiple-choice

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What is the salary of a Microsoft DP-203 certified professional?

The Average salary of different countries of Microsoft DP-203 Certified professional

  • India - 7905404 INR

  • UK - 78707 Pounds

  • United States - $104,000 USD

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

Microsoft DP-203 Exam Reference link

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

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