Why do we need to normalize a data model ?
-
to make it look good
-
to comply with the multidimensional modelling rules
-
to increase performance
-
to avoid redundancy
Normalization in data modeling is fundamentally about eliminating redundancy and preventing update anomalies. While it can improve performance in some cases, that's not the primary purpose. It's not about aesthetics or complying with multidimensional rules - those are different concerns.
Normalization organizes data into related tables so that each fact is stored only once, which eliminates redundant/duplicate data and the update anomalies that come with it. It isn't primarily about aesthetics or performance (in fact heavy normalization can hurt read performance), and multidimensional modeling actually favors deliberate denormalization (star schema), so 'avoid redundancy' is the core reason to normalize.