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What are the objectives of the Microsoft DP-420 Certification Exam?

As per the guidance of the DP-420 Dumps, there are 02 main objectives of the Microsoft DP-420 Certification Exam. The first is to understand Azure Cosmos DB architecture & components, and the second is to understand the design and implementation of cloud-native applications using Microsoft Azure Cosmos DB. Assessment of the candidate's technical knowledge and skills in the field of Azure SQL Database Administration.

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

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Following is the info about the Passing Score, Duration & Questions for the Microsoft DP-420 Exam

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:

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

Microsoft DP-420 Exam Syllabus Topics:

Section	Weight	Objectives
Design and implement data models	35-40%	- Design a data partitioning strategy 1. Choose a partitioning strategy 2. Evaluate cross-partition query cost 3. Implement synthetic partition keys 4. Choose a partition key 5. Evaluate throughput and data distribution 6. Plan for transactions with partition keys - Design and implement a non-relational data model for Azure Cosmos DB for NoSQL 1. Store multiple related entities in the same document 2. Reference between documents 3. Identify partition key, id, and unique keys 4. Denormalize data across documents 5. Store multiple entity types in the same container 6. Identify data and associated access patterns - Implement client connectivity options 1. Create database connections 2. Use Azure Cosmos DB emulator 3. Configure client-side threading and logging 4. Choose gateway or direct connectivity mode 5. Implement singleton client 6. Handle connection errors - Implement server-side programming 1. Implement user-defined functions 2. Write and deploy stored procedures 3. Implement triggers - Plan and implement sizing and scaling 1. Design resource governance and scaling 2. Evaluate throughput and storage requirements 3. Choose between serverless, provisioned, and free tier 4. Configure throughput 5. Evaluate global distribution costs - Implement data access 1. Manage transactional batch operations 2. Use SDKs for CRUD operations 3. Use consistency and query request options 4. Implement optimistic concurrency control 5. Implement SQL queries with arrays and aggregation 6. Implement patch operations
Integrate an Azure Cosmos DB solution	5-10%	- Enable analytical workloads 1. Query analytical store from Synapse 2. Configure Azure Cosmos DB Mirroring 3. Write data back from Spark 4. Enable analytical store - 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
Optimize an Azure Cosmos DB solution	15-20%	- Define and implement indexing strategy 1. Configure custom indexing policies 2. Implement composite indexes 3. Optimize index performance 4. Choose appropriate index types 5. Choose read-heavy or write-heavy indexing - Optimize query performance 1. Implement integrated cache 2. Calculate query cost 3. Adjust indexing policies 4. Retrieve request unit cost - Design and implement change feeds 1. Consume change feeds using SDK 2. Implement aggregation persistence 3. Develop Azure Functions triggers 4. Manage change feed instances
Design and implement data distribution	5-10%	- Design and implement multi-region writes 1. Choose when to use multi-region writes 2. Implement multi-region writes 3. Implement conflict resolution policies - Design and implement replication strategy 1. Define automatic failover policies 2. Perform manual failovers 3. Choose when to distribute data 4. Evaluate consistency model impacts 5. Choose a consistency model
Maintain an Azure Cosmos DB solution	25-30%	- Monitor and troubleshoot Azure Cosmos DB solutions 1. Troubleshoot throughput issues 2. Implement backup and recovery strategies 3. Monitor performance and availability 4. Monitor metrics and logs