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Certification Topics of Microsoft DP-203 Exam
Design and implement data security (10-15%)
Design and develop data processing (25-30%)
Monitor and optimize data storage and data processing (10-15%)
Design and implement data storage (40-45%)
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.
All the details of Microsoft DP-203 Exam format?
Language: English
Passing score: 75%
Exam Format: multiple-choice
Exam Duration: 130 minutes
Exam Length: 40-60 question
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Simulation test system
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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
Microsoft DP-203 Deutsch Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Monitor and optimize data solutions | 30-35% | - Optimize performance
|
| Design and implement data storage | 25-30% | - Develop data storage solutions
|
| Secure data solutions | - Ensure compliance
| |
| Develop data processing | 40-45% | - Ingest and transform data
|
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