Microsoft DP-203 Korean Exam Details & Actual Exam Questions

Exam Code/Number: DP-203 Korean
Exam Name/Title: Data Engineering on Microsoft Azure (DP-203 Korean Version)
Certification Provider: Microsoft
Corresponding Certification: Microsoft Certified: Azure Data Engineer Associate

Exam Questions: 365
Updated On: Jul,28 2026
Certification Level: Associate

Microsoft Data Engineering on Microsoft Azure (DP-203 Korean Version) Exam Questions

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Microsoft DP-203 Korean Exam Overview:

Certification Vendor:	Microsoft
Exam Name:	Data Engineering on Microsoft Azure
Exam Number:	DP-203
Exam Format:	Multiple-choice, Multiple-answer, Case studies, Scenario-based questions
Certificate Validity Period:	2 years
Passing Score:	700 (scale 100–1000)
Real Exam Qty:	40–60
Exam Duration:	150 minutes
Related Certifications:	Microsoft Certified: Azure Data Scientist Associate Microsoft Certified: Azure Database Administrator Associate
Available Languages:	English, Chinese (Simplified), Japanese, Korean, German, French, Spanish, Portuguese (Brazil), Arabic (Saudi Arabia), Russian, Chinese (Traditional), Italian, Indonesian (Indonesia)
Exam Price:	$165 USD
Recommended Training:	Azure Data Engineer Associate Training Microsoft Learn: DP-203 Learning Path
Exam Registration:	Pearson VUE Microsoft Exam Registration
Sample Questions:	Microsoft DP-203 Korean Sample Questions
Exam Way:	Online proctored or onsite at Pearson VUE test centers
Pre Condition:	No mandatory prerequisites; recommended experience: 2+ years working with Azure data services, knowledge of SQL, Python/Scala, data modeling, ETL/ELT processes
Official Syllabus URL:	https://learn.microsoft.com/en-us/credentials/certifications/exams/dp-203/

Microsoft DP-203 Korean Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Design and implement data storage	40–45%	- Design data storage structures 1. Design for data durability and availability 2. Recommend storage solutions for analytical workloads 3. Design partitioning strategies 4. Design for scalability and performance - Implement data storage 1. Manage data lifecycle and retention policies 2. Implement data lake storage 3. Create and configure data storage accounts 4. Implement relational and non-relational data stores
Topic 2: Monitor and optimize data storage and data processing	10–15%	- Optimize performance and cost 1. Tune pipelines and workloads 2. Optimize storage and compute resources 3. Improve query and processing efficiency - Monitor data solutions 1. Log and analyze activity and usage 2. Monitor pipeline execution and errors 3. Monitor storage performance and health
Topic 3: Design and develop data processing	25–30%	- Design data processing pipelines 1. Design batch processing solutions 2. Design orchestration and scheduling 3. Design real-time processing solutions 4. Design for data integration and transformation - Develop data processing solutions 1. Transform data using Spark, SQL, or other tools 2. Implement data ingestion 3. Manage data flows and dependencies 4. Implement incremental processing
Topic 4: Design and implement data security	10–15%	- Implement authentication and authorization 1. Configure identity and access management 2. Manage access to data resources - Protect data at rest and in transit 1. Implement encryption 2. Configure data masking and redaction 3. Manage data privacy and compliance