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

Microsoft DP-420日本語 Exam Syllabus Topics:

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

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