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Are you ready to take the Data Engineering on Microsoft Azure Exam

DP-203 Exam: Key Points and Focus Areas

The Microsoft Data Platform, or MDP, is a collection of products and services that primarily target companies whose business involves large volumes of data. These companies are often referred to as data-driven businesses. The MDP helps such businesses store, process, and analyze the massive amounts of data that their operations produce. The Microsoft Data Platform Certification (Microsoft DP-203) exam tests a candidate's knowledge of the Microsoft technologies that are used to build a cloud computing infrastructure for Big Data analytics. Free demo material that helps with the preparation for the DP-203 exam includes sample questions and answers, practice exams, and a training guide. Microsoft DP-203 Dumps provide all the test-taking tools necessary for passing the DP-203 exam, including a test engine and a simulation mode. If you are reading this article it means you are interested in pursuing a Microsoft certification path or already have one. Great! You've taken an important first step to become a Data Engineer on Microsoft Azure certification.

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

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This exam measures your ability to accomplish the following technical tasks: design and implement data storage; design and develop data processing; design and implement data security; and monitor and optimize data storage and data processing.

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Data Engineering on Microsoft Azure Exam Certification Details:

Number of Questions40-60
Duration150 mins
Exam Price$165 (USD)
Passing Score700 / 1000
Sample QuestionsData Engineering on Microsoft Azure Sample Questions
Schedule ExamPearson VUE
Exam NameMicrosoft Certified - Azure Data Engineer Associate
Exam CodeDP-203
Books / TrainingDP-203T00: Data Engineering on Microsoft Azure

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Microsoft DP-203日本語 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: 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 Spark in Azure Databricks
          • 2. Use SQL-based transformations
            Topic 2: Monitor and optimize data solutions30-35%- Optimize performance
            • 1. Optimize data storage performance
              • 2. Optimize query performance in Synapse
                - Monitor data processing
                • 1. Monitor pipelines using Azure Monitor
                  • 2. Troubleshoot data workflows
                    Topic 3: Design and implement data storage25-30%- Design data storage structures
                    • 1. Design a data serialization format strategy
                      • 2. Recommend appropriate storage accounts and services
                        • 3. Design a data partitioning strategy
                          - 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)
                                Topic 4: 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

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