Depending on the purpose, we may need to create either a conceptual, logical, or physical data model. Find out the differences and use cases for each one. Data modeling implies identifying and defining entities and their relationships for a business solution. It requires a good understanding of the desired business outcome and is the foundation for creating a robust software solution. The different model types (conceptual, logical, and physical) have different levels of detail and are used at different stages of the software development process.
Are you a student or a beginning data modeler who wants to learn more about data modeling? Let’s start learning with the conceptual data model – the least detailed of the three models. In this article, we’ll discuss the conceptual data model using some real-world examples. As you know, data modeling is the process of describing real-world data – its relationships, features, and attributes – in a structured document like an ER (entity-relationship) diagram.
This article will lead you through the differences between the conceptual, logical, and physical data models. It will also show you how to create each one. What are conceptual, logical, and physical data models? What do they do, and what are the differences between them? That’s what I’ll answer in this article. It won’t be only theory; I’ll also show you how to create different data models using Vertabelo.