MEAPSA

Design a data partitioning strategy

Identify strategies for managing relationships between data entities, such as customers and sales data. Improve data-model performance and scaling by pre-aggregating and denormalizing your data. Use change-feed to maintain your data's referential integrity.

Developer

Azure

Cosmos DB

Module Objectives

At the completing this module we will learn:

Manage relationships between data entities by using advanced modeling and partitioning strategies.
Maintain the referential integrity of your data by using change feed.
Implement pre-aggregating and denormalizing data strategies to improve data-model performance and scaling.
Optimizing storage and compute by mixing entity types in a single container

Units

Introduction min
Denormalize data in your model min
Manage referential integrity by using change feed min
Combine multiple entities in the same container min
Denormalize aggregates in the same container min
Finalize the data model min
Exercise advanced modeling patterns min
Knowledge check min
Summary min

Prerequisites

Familiarity with Azure Cosmos DB concepts such as databases, containers, documents, and throughput (request units per second [RU/s]).
Familiarity with navigating Azure Cosmos DB resources and data by using Data Explorer in the Azure portal, running queries, and viewing query stats in results.
Familiarity with basic modeling and partitioning strategies, such as embedding or referencing data in entities.
Familiarity with Azure Cosmos DB .NET SDK v3.
Familiarity with Azure Cosmos DB change feed.