3NF and Dimensional Data Modeling: Concepts, Pros, Cons, and Use Cases

Data modeling is a very important aspect of database design and plays a crucial role in designing the structure of data for various analytical and operational needs. Two popular approaches in data modeling are the Third Normal Form (3NF) and Dimensional Data Modeling. These methods were created by different pioneers and purpose to different use cases, each with its own set of advantages and drawbacks. In this article, I will simplistically explore the concepts, pros, cons, and use cases of 3NF and Dimensional Data Modeling, and provide examples to illustrate their applications.

Third Normal Form (3NF) Data Modelling

3NF is a database normalization technique introduced by Edgar F. Codd, a computer scientist and the inventor of the relational database model. It’s based on the principles of data normalization, which aim to reduce data redundancy and improve data integrity. In 3NF, a database schema is designed to eliminate transitive dependencies and ensure that each attribute is functionally dependent on the primary key.

Pros:

- Data Integrity: 3NF ensures that data is stored in a consistent and non-redundant manner, minimizing the risk of anomalies like update anomalies, insertion anomalies, and deletion anomalies.