The process of structuring data in a database is known as normalisation. This includes generating tables and defining relationships between them according to rules aimed to secure data while also allowing the database to be more flexible by removing redundancy and inconsistent dependencies.
Normalization provides each variable equal weights/importance, ensuring that no single variable biases model performance in one direction simply because it is larger. Clustering algorithms, for example, utilise distance measurements to determine whether or not an observation belongs in a certain cluster.
It vastly improves model precision. Normalization provides each variable equal weights/importance, ensuring that no single variable biases model performance in one direction simply because it is larger.