Data Modeling and Partitioning Patterns in Azure Cosmos DB

Unlock the power of Azure Cosmos DB with effective data modeling! This course, Data Modeling and Partitioning Patterns in Azure Cosmos DB, guides you through designing optimal data models for Microsoft's globally distributed, multi-model database service on Azure.

Learn how to transform your existing data structures. We'll walk you through the process of adapting a traditional relational schema to a Cosmos DB data model, using the familiar AdventureWorks sample database as a practical example.

Key topics include:

• Cosmos DB Partitioning: Understand the fundamentals of partitioning and throughput to ensure high performance and scalability for your applications.
• Non-Relational Data Modeling: Explore best practices for non-relational data modeling, including:
  • Embedding vs. Referencing: Learn when to embed data and when to reference it for optimal data organization.
  • Schema-Free Data Structures: Discover how to leverage Cosmos DB's schema flexibility.
  • Data Denormalization: Master data denormalization techniques to improve query performance.
• Advanced Techniques: Dive into utilizing the Change Feed API, Azure Functions, and transactionalized stored procedures for data manipulation and synchronization within Azure Cosmos DB.

By the end of this course, you'll be equipped with the skills to create highly performant and scalable data models in Azure Cosmos DB, maximizing the benefits of this powerful, horizontally partitioned database. Master data modeling for Azure Cosmos DB and build robust, future-proof applications.