Data Engineering on Microsoft Azure (DP-203 Deutsch Version): DP-203 Exam

"Data Engineering on Microsoft Azure (DP-203 Deutsch Version)", also known as DP-203 exam, is a Microsoft Certification. With the complete collection of questions and answers, UpdateDumps has assembled to take you through 365 Q&As to your DP-203 Exam preparation. In the DP-203 exam resources, you will cover every field and category in Microsoft Certified: Azure Data Engineer Associate Certification helping to ready you for your successful Microsoft Certification.

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  • Updated on: Jul 27, 2026
  • No. of Questions: 365 Questions & Answers

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  • Updated on: Jul 27, 2026
  • No. of Questions: 365 Questions & Answers

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Data Engineering on Microsoft Azure Exam Certification Details:

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

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All the details of Microsoft DP-203 Exam format?

  • Language: English

  • Exam Duration: 130 minutes

  • Passing score: 75%

  • Exam Length: 40-60 question

  • Exam Format: multiple-choice

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

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How to schedule for Microsoft DP-203 Exam

The DP-203 exam is offered through Pearson VUE test centers at various locations across the country. To register for the DP-203 exam, follow these steps: Go to Microsoft DP-203 Exam.

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.

Microsoft DP-203 Deutsch Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Design and implement data storage40–45%- Implement data storage
  • 1. Implement relational and non-relational data stores
    • 2. Create and configure data storage accounts
      • 3. Manage data lifecycle and retention policies
        • 4. Implement data lake storage
          - Design data storage structures
          • 1. Recommend storage solutions for analytical workloads
            • 2. Design for data durability and availability
              • 3. Design for scalability and performance
                • 4. Design partitioning strategies
                  Topic 2: Design and implement data security10–15%- Protect data at rest and in transit
                  • 1. Implement encryption
                    • 2. Configure data masking and redaction
                      • 3. Manage data privacy and compliance
                        - Implement authentication and authorization
                        • 1. Configure identity and access management
                          • 2. Manage access to data resources
                            Topic 3: Design and develop data processing25–30%- Develop data processing solutions
                            • 1. Manage data flows and dependencies
                              • 2. Implement data ingestion
                                • 3. Implement incremental processing
                                  • 4. Transform data using Spark, SQL, or other tools
                                    - Design data processing pipelines
                                    • 1. Design orchestration and scheduling
                                      • 2. Design real-time processing solutions
                                        • 3. Design batch processing solutions
                                          • 4. Design for data integration and transformation
                                            Topic 4: Monitor and optimize data storage and data processing10–15%- Optimize performance and cost
                                            • 1. Improve query and processing efficiency
                                              • 2. Tune pipelines and workloads
                                                • 3. Optimize storage and compute resources
                                                  - Monitor data solutions
                                                  • 1. Log and analyze activity and usage
                                                    • 2. Monitor storage performance and health
                                                      • 3. Monitor pipeline execution and errors

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