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

DP-203 Deutsch testking pdf

Exam Code: DP-203-Deutsch

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

Updated: Oct 10, 2026

Q & A: 365 Questions and Answers

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

Certification Topics of Microsoft DP-203 Exam

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

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

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

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

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

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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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DP-203 Deutsch exam dumps

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Skills measured

  • Design and implement data storage (40-45%)
  • Design and develop data processing (25-30%)
  • Monitor and optimize data storage and data processing (10-15%)
  • Design and implement data security (10-15%)

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Microsoft DP-203 Deutsch Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Design and Implement Data Security10-15%- Implement data security
  • 1. Manage sensitive data
  • 2. Implement data encryption
  • 3. Configure authentication and authorization
Topic 2: Design and Develop Data Processing25-30%- Develop batch processing solutions
  • 1. Implement Azure Databricks notebooks
  • 2. Develop Azure Data Factory pipelines
  • 3. Transform data using Apache Spark
- Develop stream processing solutions
  • 1. Process streaming data with Event Hubs
  • 2. Implement Azure Stream Analytics
Topic 3: Monitor and Optimize Data Storage and Processing10-15%- Optimize performance
  • 1. Optimize query performance
  • 2. Optimize data partitioning and indexing
- Monitor data solutions
  • 1. Monitor pipeline execution
  • 2. Monitor Spark workloads
Topic 4: Design and Implement Data Storage40-45%- Implement data storage solutions
  • 1. Implement Azure Data Lake Storage
  • 2. Implement Azure Synapse Analytics storage
  • 3. Implement Delta Lake
- Design a data storage structure
  • 1. Design partitioning strategies
  • 2. Design a lakehouse architecture
  • 3. Design a data warehouse schema

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