Data modeling is critical for efficient data storage and retrieval, and choosing the right data model is crucial for building scalable and performant applications. In this talk, we will explore best practices for designing document data models in MongoDB, including denormalization and schema validation. We will also cover common design patterns for document data models, such as hierarchical, relational, and embedded data models. We will discuss the benefits and limitations of MongoDB's document model and highlight tips for optimizing query performance. Additionally, we will explore the concepts of polymorphism, embedding, and referencing in MongoDB and provide real-world examples of when to use each approach. Join us for an in-depth exploration of MongoDB data modeling and learn how to design efficient, scalable, and flexible data models for your application.

Although this talk covers MongoDB, it should not be confused with a promotion or sales pitch of any kind. The concepts apply to all document-oriented databases.