Microsoft DP-420 Korean : Designing and Implementing Cloud-Native Applications Using Microsoft Azure Cosmos DB (DP-420 Korean Version)

  • Exam Code: DP-420-KR
  • Exam Name: Designing and Implementing Cloud-Native Applications Using Microsoft Azure Cosmos DB (DP-420 Korean Version)
  • Updated: Jul 29, 2026
  • Q & A: 281 Questions and Answers

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About Microsoft DP-420 Korean Exam Questions

What are the prerequisites to take the Microsoft DP-420 Certification Exam?

There are no prerequisites for the Microsoft DP-420 Certification Exam.

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Information about the Passing Score, Duration & Questions for the Microsoft DP-420 Exam is given in the DP-420 Dumps. The overview of that info is as given below:

  • The passing scores: 70%
  • Languages: English
  • Number of Questions: 40-60
  • Time Duration: 60 minutes

Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/dp-420?WT.mc_id=Azure_blog-wwl

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The salary of the Microsoft DP-420 Certified professional depends on the type of the organization, company size, location, and the number of years of experience. It also depends on the job title of the Microsoft DP-420 certified professional. The average salary a Microsoft DP-420 certified professional can get, after passing the exam with the help of the DP-420 Dumps is as follows:

  • In Sweden: 37,000 SEK
  • In the United States: 85,000 USD
  • In India: 45,000 INR
  • In Germany: 43,000 EUR
  • In the United Kingdom: 56,000 GBP

Microsoft DP-420 Korean Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Design and implement data models35-40%- Design and implement a non-relational data model for Azure Cosmos DB for NoSQL
  • 1. Store multiple related entities in the same document
  • 2. Identify partition key, id, and unique keys
  • 3. Reference between documents
  • 4. Identify data and associated access patterns
  • 5. Store multiple entity types in the same container
  • 6. Denormalize data across documents
- Plan and implement sizing and scaling
  • 1. Design resource governance and scaling
  • 2. Evaluate global distribution costs
  • 3. Choose between serverless, provisioned, and free tier
  • 4. Configure throughput
  • 5. Evaluate throughput and storage requirements
- Design a data partitioning strategy
  • 1. Evaluate cross-partition query cost
  • 2. Plan for transactions with partition keys
  • 3. Evaluate throughput and data distribution
  • 4. Implement synthetic partition keys
  • 5. Choose a partition key
  • 6. Choose a partitioning strategy
- Implement server-side programming
  • 1. Implement triggers
  • 2. Write and deploy stored procedures
  • 3. Implement user-defined functions
- Implement data access
  • 1. Use consistency and query request options
  • 2. Implement SQL queries with arrays and aggregation
  • 3. Use SDKs for CRUD operations
  • 4. Implement patch operations
  • 5. Manage transactional batch operations
  • 6. Implement optimistic concurrency control
- Implement client connectivity options
  • 1. Configure client-side threading and logging
  • 2. Create database connections
  • 3. Use Azure Cosmos DB emulator
  • 4. Choose gateway or direct connectivity mode
  • 5. Implement singleton client
  • 6. Handle connection errors
Topic 2: Design and implement data distribution5-10%- Design and implement replication strategy
  • 1. Choose when to distribute data
  • 2. Evaluate consistency model impacts
  • 3. Define automatic failover policies
  • 4. Perform manual failovers
  • 5. Choose a consistency model
- Design and implement multi-region writes
  • 1. Implement conflict resolution policies
  • 2. Choose when to use multi-region writes
  • 3. Implement multi-region writes
Topic 3: Optimize an Azure Cosmos DB solution15-20%- Design and implement change feeds
  • 1. Develop Azure Functions triggers
  • 2. Consume change feeds using SDK
  • 3. Implement aggregation persistence
  • 4. Manage change feed instances
- Optimize query performance
  • 1. Adjust indexing policies
  • 2. Implement integrated cache
  • 3. Retrieve request unit cost
  • 4. Calculate query cost
- Define and implement indexing strategy
  • 1. Choose read-heavy or write-heavy indexing
  • 2. Configure custom indexing policies
  • 3. Implement composite indexes
  • 4. Optimize index performance
  • 5. Choose appropriate index types
Topic 4: Maintain an Azure Cosmos DB solution25-30%- Monitor and troubleshoot Azure Cosmos DB solutions
  • 1. Monitor metrics and logs
  • 2. Monitor performance and availability
  • 3. Troubleshoot throughput issues
  • 4. Implement backup and recovery strategies
Topic 5: Integrate an Azure Cosmos DB solution5-10%- Implement solutions across services
  • 1. Integrate Azure Functions and Event Hubs
  • 2. Implement Azure AI Search integration
  • 3. Use Change Feed for denormalization
  • 4. Enforce referential integrity
  • 5. Aggregate and archive data
- Enable analytical workloads
  • 1. Configure Azure Cosmos DB Mirroring
  • 2. Query analytical store from Synapse
  • 3. Write data back from Spark
  • 4. Enable analytical store

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