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Microsoft Certified: Azure Cosmos DB Developer Specialty (DP420)

In the ever-evolving landscape of data science, Microsoft's DP-420 course stands out as a pivotal resource, offering individuals an opportunity to delve into the intricacies of designing and implementing data solutions on Azure. This comprehensive course is designed to equip participants with the skills necessary to architect robust and scalable data solutions, leveraging the power of Microsoft Azure services. 

This four-day Microsoft certified course teaches developers how to create application using the SQL API and SDK for Azure Cosmos DB. Students will learn how to write efficient queries, create indexing policies, manage and provisioned resources, and perform common operations with the SDK.

This training is a comprehensive preparation for the DP-420: Designing and Implementing Cloud-Native Applications Using Microsoft Azure Cosmos DB exam to earn the Microsoft Certified: Azure Cosmos DB Developer Specialty.

Microsoft

Applicable solutions

Public class

Virtual classroom
Planned datePlanned date
July 1 2024
$2895$
 
English
Virtual classroom
Planned datePlanned date
August 12 2024
$2895$
 
English
Virtual classroom
Planned datePlanned date
September 16 2024
$2895$
 
English
Virtual classroom
Planned datePlanned date
October 14 2024
$2895$
 
English
2895$
Duration: 
4 days / 28 hours

Private class

Virtual classroom
Minimum no. of participants: 5
4 days / 28 hours
Price on request
English or French
Training plan: 

Designing and Implementing Cloud-Native Applications Using Microsoft Azure Cosmos DB (DP-420T00)

Module 1: Get started with Azure Cosmos DB for NoSQL

  • Introduction to Azure Cosmos DB for NoSQL
  • Try Azure Cosmos DB for NoSQL

Module 2: Plan and implement Azure Cosmos DB for NoSQL

  • Plan Resource Requirements
  • Configure Azure Cosmos DB for NoSQL database and containers
  • Move data into and out of Azure Cosmos DB for NoSQL

Module 3: Connect to Azure Cosmos DB for NoSQL with the SDK

  • Use the Azure Cosmos DB for NoSQL SDK
  • Configure the Azure Cosmos DB for NoSQL SDK

Module 4: Access and manage data with the Azure Cosmos DB for NoSQL SDKs

  • Implement Azure Cosmos DB for NoSQL point operations
  • Perform cross-document transactional operations with the Azure Cosmos DB for NoSQL
  • Process bulk data in Azure Cosmos DB for NoSQL

Module 5: Execute queries in Azure Cosmos DB for NoSQL

  • Query the Azure Cosmos DB for NoSQL
  • Author complex queries with the Azure Cosmos DB for NoSQL

Module 6: Define and implement an indexing strategy for Azure Cosmos DB for NoSQL

  • Define indexes in Azure Cosmos DB for NoSQL
  • Customize indexes in Azure Cosmos DB for NoSQL

Module 7: Integrate Azure Cosmos DB for NoSQL with Azure services

  • Consume an Azure Cosmos DB for NoSQL change feed using the SDK
  • Handle events with Azure Functions and Azure Cosmos DB for NoSQL change feed
  • Search Azure Cosmos DB for NoSQL data with Azure Cognitive Search

Module 8: Implement a data modeling and partitioning strategy for Azure Cosmos DB for NoSQL

  • Implement a non-relational data model
  • Design a data partitioning strategy

Module 9: Design and implement a replication strategy for Azure Cosmos DB for NoSQL

  • Configure replication and manage failovers in Azure Cosmos DB
  • Use consistency models in Azure Cosmos DB for NoSQL
  • Configure multi-region write in Azure Cosmos DB for NoSQL

Module 10: Optimize query and operation performance in Azure Cosmos DB for NoSQL

  • Customize an indexing policy in Azure Cosmos DB for NoSQL
  • Measure index performance in Azure Cosmos DB for NoSQL
  • Implement integrated cache in Azure Cosmos DB for NoSQL

Module 11: Monitor and troubleshoot an Azure Cosmos DB for NoSQL solution

  • Measure performance in Azure Cosmos DB for NoSQL
  • Monitor responses and events in Azure Cosmos DB for NoSQL
  • Implement backup and restore for Azure Cosmos DB for NoSQL
  • Implement security in Azure Cosmos DB for NoSQL

Module 12: Manage an Azure Cosmos DB for NoSQL solution using DevOps practices

  • Write management scripts for Azure Cosmos DB for NoSQL
  • Create resource template for Azure Cosmos DB for NoSQL

Module 13: Create server-side programming constructs in Azure Cosmos DB for NoSQL

  • Build multi-item transactions with the Azure Cosmos DB for NoSQL
  • Expand query and transaction functionality in Azure Cosmos DB for NoSQL
Exclusives: 
Prerequisites: 

Before attending this course, students must have:

  • Knowledge of Microsoft Azure and ability to navigate the Azure portal (AZ-900 equivalent)
  • Experience writing in an Azure-supported language at the intermediate level. (C#, JavaScript, Python, or Java)
  • Ability to write code to connect and perform operations on a SQL or NoSQL database product. (SQL Server, Oracle, MongoDB, Cassandra or similar)
Credentials information: 

Exam Characteristics  

  • Exam code: DP-420  
  • Exam Title: Designing and Implementing Cloud-Native Applications Using Microsoft Azure Cosmos DB  
  • Exam Duration: 120 minutes   
  • Number of Questions: 40 to 60   
  • Question Formats: Multiple-choice, multiple-answer, scenario-based  
  • Passing Score: 700 out of 1000  
  • Cost: $0 (included in your training)  

Exam Topics  

  • Design and implement data models  
  • Design and implement data distribution 
  • Integrate an Azure Cosmos DB solution  
  • Optimize an Azure Cosmos DB solution  
  • Maintain an Azure Cosmos DB solution  
  • All details...   
Audiences: 

Course Overview 

The DP-420 course, titled "Cloud-Native Applications Using Microsoft Azure Cosmos DB" provides a deep dive into the world of cloud-native data solutions. It caters to data engineers, architects, and IT professionals seeking to harness the capabilities of Azure Cosmos DB and Azure Storage for designing and implementing efficient, high-performance data solutions. 

Key Learning Objectives 

  • Azure Cosmos DB Fundamentals - The course initiates with a comprehensive exploration of Azure Cosmos DB, delving into its fundamentals, data modeling, and best practices for creating globally distributed, multi-model databases. 

  • Azure Storage Optimization - Participants learn how to optimize Azure Storage solutions for scalability, performance, and cost-efficiency. This includes understanding blob storage, table storage, queue storage, and file storage services. 

  • Data Solution Design - The DP-420 course focuses on the art of designing effective data solutions. Participants gain insights into designing data storage, data processing, and data integration solutions tailored to specific business requirements. 

  • Scaling and Performance Tuning - Scaling and performance are critical aspects of any data solution. The course equips participants with the knowledge and skills to scale solutions effectively and fine-tune performance for optimal results. 

  • Security and Compliance - Security is paramount in data solutions. The course covers best practices for securing data, implementing authentication and authorization mechanisms, and ensuring compliance with regulatory standards. 

  • Practical Application through Projects - One distinctive feature of the DP-420 course is its emphasis on practical application. Participants engage in hands-on projects, applying theoretical knowledge to real-world scenarios. These projects involve designing and implementing data solutions using Azure Cosmos DB and Azure Storage, providing valuable, job-relevant experience. 

Certification and Career Impact 

Successful completion of the DP-420 course can lead to the Microsoft Certified: Azure Cosmos DB Developer Specialty certification. This certification not only validates expertise in designing and implementing cloud-native data solutions but also enhances career prospects in the competitive field of data engineering and architecture. 

Conclusion

In conclusion, Microsoft's DP-420 course is a gateway to mastering cloud-native data solutions on Azure. By combining theoretical insights with hands-on experience, this course empowers data professionals to architect and implement efficient, scalable, and secure data solutions, making them invaluable assets in the ever-expanding realm of data science. 

Common Questions about DP 420 (FAQ) 

What is the difference between Azure DB and Cosmos DB?  

Azure DB is a broad term encompassing various Azure database services, while Cosmos DB is a specialized, globally distributed, multi-model database service on Azure. Cosmos DB supports multiple data models, including document, key-value, graph, and column-family, providing unparalleled flexibility for diverse application requirements. Its global distribution ensures low-latency access to data worldwide, setting it apart from traditional Azure database offerings. 

Is Azure Cosmos DB SQL or NoSQL?  

Azure Cosmos DB is a versatile multi-model database service that accommodates both SQL and NoSQL data models. This adaptability allows developers to choose the most suitable data model for their application, whether it follows a structured SQL approach or embraces the flexibility of NoSQL for unstructured or semi-structured data. This unique capability positions Azure Cosmos DB as a comprehensive solution catering to a wide range of application scenarios. 

Which is the native API for Cosmos DB?  

Azure Cosmos DB provides multiple APIs, each tailored to support specific data models. However, the SQL API, formerly known as DocumentDB, is considered the native API for Cosmos DB. This API is designed to seamlessly integrate with JSON data structures and offers a familiar SQL-like language for querying and manipulating data. Choosing the SQL API ensures optimal compatibility and performance within the Cosmos DB environment. 

What type of cloud service is Azure Cosmos DB?  

Azure Cosmos DB is a fully managed, globally distributed, and multi-model database service that operates within the Platform as a Service (PaaS) model in cloud computing. As a PaaS offering, Cosmos DB abstracts the complexities of database management, allowing developers to focus on building applications without the burden of infrastructure management. Its global distribution, automatic scalability, and comprehensive support for various data models make it a robust and versatile solution for modern cloud-based applications. 

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