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Data Engineering on Microsoft Azure Exam Certification Details:

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

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Languages: English, Chinese (Simplified), Japanese, Korean

Retirement date: none

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

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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.

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

Microsoft DP-203 Deutsch Exam Syllabus Topics:

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