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Microsoft DP-420 Exam Topics, Blueprint and Syllabus

Designing and Implementing Cloud-Native Applications Using Microsoft Azure Cosmos DB

Last Update November 22, 2024
Total Questions : 128

Our Microsoft Certified: Azure Cosmos DB Developer Specialty DP-420 exam questions and answers cover all the topics of the latest Designing and Implementing Cloud-Native Applications Using Microsoft Azure Cosmos DB exam, See the topics listed below. We also provide Microsoft DP-420 exam dumps with accurate exam content to help you prepare for the exam quickly and easily. Additionally, we offer a range of Microsoft DP-420 resources to help you understand the topics covered in the exam, such as Microsoft Certified: Azure Cosmos DB Developer Specialty video tutorials, DP-420 study guides, and DP-420 practice exams. With these resources, you can develop a better understanding of the topics covered in the exam and be better prepared for success.

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Microsoft DP-420 Exam Overview :

Exam Name Designing and Implementing Cloud-Native Applications Using Microsoft Azure Cosmos DB
Exam Code DP-420
Actual Exam Duration The Microsoft DP-420 exam is a one-hour exam that consists of 40-60 questions.
What exam is all about Microsoft DP-420 is a certification exam for the Microsoft Azure Data Platform Solutions certification. It is designed to test a candidate's knowledge and skills in designing, implementing, and managing data platform solutions using Microsoft Azure technologies. The exam covers topics such as data storage, data security, data integration, data analytics, and data governance.
Passing Score required The passing score for the Microsoft DP-420 exam is 700 out of 1000.
Competency Level required The Microsoft DP-420 exam is designed for IT professionals who have a basic understanding of data protection and data governance concepts. It is recommended that candidates have at least one year of experience working with data protection and data governance solutions.
Questions Format The Microsoft DP-420 exam consists of multiple-choice and case study-style questions.
Delivery of Exam Microsoft DP-420 exam is available in two delivery formats: online proctored exam and on-site proctored exam.
Language offered English, Japanese, Chinese (Simplified), Korean, German, French, Spanish, Portuguese (Brazil), Chinese (Traditional), Italian
Cost of exam The cost of the Microsoft DP-420 exam is $165 USD.
Target Audience The Microsoft DP-420 is designed for IT professionals who need to develop and deploy data-driven solutions. It is suitable for those who are familiar with the Microsoft SQL Server platform and have experience with database development, administration, and maintenance. It is also suitable for those who are looking to gain a deeper understanding of the Microsoft SQL Server platform and its capabilities.
Average Salary in Market The average salary for a Microsoft Certified DP-420 professional is around $90,000 per year. However, salaries can vary depending on experience, location, and other factors.
Testing Provider Microsoft does not provide the DP-420 exam for testing. The DP-420 exam is a certification exam that is used to assess a candidate's knowledge and skills related to Microsoft Data Platform technologies. Candidates must register and pay for the exam through the Microsoft Learning website in order to take the exam.
Recommended Experience Microsoft recommends that candidates have at least six months of experience working with data warehousing and analytics solutions, including experience with Azure Data Factory, Azure Data Lake, Azure Synapse Analytics, and Power BI. Candidates should also have experience with data modeling, data integration, and data security.
Prerequisite The Microsoft DP-420 exam does not have any prerequisites. However, it is recommended that candidates have a working knowledge of data warehousing concepts, data modeling, and data analysis. Additionally, it is recommended that candidates have experience with Microsoft Azure Data Factory, Azure Data Lake, and Azure Synapse Analytics.
Retirement (If Applicable) Microsoft does not provide an expected retirement date for the DP-420 exam. However, Microsoft recommends that you take the exam before it is retired to ensure that you have the most up-to-date knowledge and skills.
Certification Track (RoadMap): The Microsoft DP-420 exam is part of the Microsoft Certified: Data Analyst Associate certification track. This certification track is designed to help individuals demonstrate their skills in data analysis, data modeling, and data visualization. The DP-420 exam is the final exam in the certification track and covers topics such as data analysis, data modeling, data visualization, and data governance. Passing the DP-420 exam will earn the individual the Microsoft Certified: Data Analyst Associate certification.
Official Information https://docs.microsoft.com/en-us/learn/certifications/exams/dp-420?WT.mc_id=Azure_blog-wwl
See Expected Questions Microsoft DP-420 Expected Questions in Actual Exam
Take Self-Assessment Use Microsoft DP-420 Practice Test to Assess your preparation - Save Time and Reduce Chances of Failure

Microsoft DP-420 Exam Topics :

Section Weight Objectives
Design and Implement Data Models 35–40% Design and implement a non-relational data model for Azure Cosmos DB Core API
  • develop a design by storing multiple entity types in the same container
  • develop a design by storing multiple related entities in the same document
  • develop a model that denormalizes data across documents
  • develop a design by referencing between documents
  • identify primary and unique keys
  • identify data and associated access patterns
  • specify a default TTL on a container for a transactional store
Design a data partitioning strategy for Azure Cosmos DB Core API
  • choose a partition strategy based on a specific workload
  • choose a partition key
  • plan for transactions when choosing a partition key
  • evaluate the cost of using a cross-partition query
  • calculate and evaluate data distribution based on partition key selection
  • calculate and evaluate throughput distribution based on partition key selection
  • construct and implement a synthetic partition key
  • design partitioning for workloads that require multiple partition keys
Plan and implement sizing and scaling for a database created with Azure Cosmos DB
  • evaluate the throughput and data storage requirements for a specific workload
  • choose between serverless and provisioned models
  • choose when to use database-level provisioned throughput
  • design for granular scale units and resource governance
  • evaluate the cost of the global distribution of data
  • configure throughput for Azure Cosmos DB by using the Azure portal
Implement client connectivity options in the Azure Cosmos DB SDK
  • choose a connectivity mode (gateway versus direct)
  • implement a connectivity mode
  • create a connection to a database
  • enable offline development by using the Azure Cosmos DB emulator
  • handle connection errors
  • implement a singleton for the client
  • specify a region for global distribution
  • configure client-side threading and parallelism options
  • enable SDK logging
Implement data access by using the Azure Cosmos DB SQL language
  • implement queries that use arrays, nested objects, aggregation, and ordering
  • implement a correlated subquery
  • implement queries that use array and type-checking functions
  • implement queries that use mathematical, string, and date functions
  • implement queries based on variable data
Implement data access by using SQL API SDKs
  • choose when to use a point operation versus a query operation
  • implement a point operation that creates, updates, and deletes documents
  • implement an update by using a patch operation
  • manage multi-document transactions using SDK Transactional Batch
  • perform a multi-document load using SDK Bulk
  • implement optimistic concurrency control using ETags
  • implement session consistency by using session tokens
  • implement a query operation that includes pagination
  • implement a query operation by using a continuation token
  • handle transient errors and 429s
  • specify TTL for a document
  • retrieve and use query metrics
Implement server-side programming in Azure Cosmos DB Core API by using JavaScript
  • write, deploy, and call a stored procedure
  • design stored procedures to work with multiple items transactionally
  • implement triggers
  • implement a user-defined function
Design and Implement Data Distribution 5–10% Design and implement a replication strategy for Azure Cosmos DB
  • choose when to distribute data
  • define automatic failover policies for regional failure for Azure Cosmos DB Core API
  • perform manual failovers to move single master write regions
  • choose a consistency model
  • identify use cases for different consistency models
  • evaluate the impact of consistency model choices on availability and associated RU cost
  • evaluate the impact of consistency model choices on performance and latency
  • specify application connections to replicated data
Design and implement multi-region write
  • choose when to use multi-region write
  • implement multi-region write
  • implement a custom conflict resolution policy for Azure Cosmos DB Core API
Integrate an Azure Cosmos DB Solution 5–10% Enable Azure Cosmos DB analytical workloads
  • enable Azure Synapse Link
  • choose between Azure Synapse Link and Spark Connector
  • enable the analytical store on a container
  • enable a connection to an analytical store and query from Azure Synapse Spark or Azure Synapse SQL
  • perform a query against the transactional store from Spark
  • write data back to the transactional store from Spark
Implement solutions across services
  • integrate events with other applications by using Azure Functions and Azure Event Hubs
  • denormalize data by using Change Feed and Azure Functions
  • enforce referential integrity by using Change Feed and Azure Functions
  • aggregate data by using Change Feed and Azure Functions, including reporting
  • archive data by using Change Feed and Azure Functions
  • implement Azure Cognitive Search for an Azure Cosmos DB solution
Optimize an Azure Cosmos DB Solution 15–20% Optimize query performance in Azure Cosmos DB Core API
  • adjust indexes on the database
  • calculate the cost of the query
  • retrieve request unit cost of a point operation or query
  • implement Azure Cosmos DB integrated cache
Design and implement change feeds for an Azure Cosmos DB Core API
  • develop an Azure Functions trigger to process a change feed
  • consume a change feed from within an application by using the SDK
  • manage the number of change feed instances by using the change feed estimator
  • implement denormalization by using a change feed
  • implement referential enforcement by using a change feed
  • implement aggregation persistence by using a change feed
  • implement data archiving by using a change feed
Define and implement an indexing strategy for an Azure Cosmos DB Core API
  • choose when to use a read-heavy versus write-heavy index strategy
  • choose an appropriate index type
  • configure a custom indexing policy by using the Azure portal
  • implement a composite index
  • optimize index performance
Maintain an Azure Cosmos DB Solution 25–30% Monitor and troubleshoot an Azure Cosmos DB solution
  • evaluate response status code and failure metrics
  • monitor metrics for normalized throughput usage by using Azure Monitor
  • monitor server-side latency metrics by using Azure Monitor
  • monitor data replication in relation to latency and availability
  • configure Azure Monitor alerts for Azure Cosmos DB
  • implement and query Azure Cosmos DB logs
  • monitor throughput across partitions
  • monitor distribution of data across partitions
  • monitor security by using logging and auditing
Implement backup and restore for an Azure Cosmos DB solution
  • choose between periodic and continuous backup
  • configure periodic backup
  • configure continuous backup and recovery
  • locate a recovery point for a point-in-time recovery
  • recover a database or container from a recovery point
Implement security for an Azure Cosmos DB solution
  • choose between service-managed and customer-managed encryption keys
  • configure network-level access control for Azure Cosmos DB
  • configure data encryption for Azure Cosmos DB
  • manage control plane access to Azure Cosmos DB by using Azure role-based accesscontrol (RBAC)
  • manage data plane access to Azure Cosmos DB by using keys
  • manage data plane access to Azure Cosmos DB by using Azure Active Directory
  • configure Cross-Origin Resource Sharing (CORS) settings
  • manage account keys by using Azure Key Vault
  • implement customer-managed keys for encryption
  • implement Always Encrypted
Implement data movement for an Azure Cosmos DB solution
  • choose a data movement strategy
  • move data by using client SDK bulk operations
  • move data by using Azure Data Factory and Azure Synapse pipelines
  • move data by using a Kafka connector
  • move data by using Azure Stream Analytics
  • move data by using the Azure Cosmos DB Spark Connector
Implement a DevOps process for an Azure Cosmos DB solution
  • choose when to use declarative versus imperative operations
  • provision and manage Azure Cosmos DB resources by using Azure Resource Manager templates (ARM templates)
  • migrate between standard and autoscale throughput by using PowerShell or Azure CLI
  • initiate a regional failover by using PowerShell or Azure CLI
  • maintain index policies in production by using ARM templates