Normalization is not always fun, and even in 1989 someone by the name of Marc Rettig tried to make it more fun and easy to absorb. He must have thought, "everybody loves puppies", let's make everybody love normalization by using puppies as an example. Naturally he was right, everybody loves puppies. :-P

Abstract Models are a technical choice to save effort in managing code and modeling effort. There's an advantage in re-use of elements, but also a disadvantage in the need for more rules, potentially more code, and harder to understand. The latter seems counter intuitive, but let this article explain using a simplified example of names.

Why Fact Oriented Modeling?

Fact Oriented Modeling is a data modeling approach which is more business oriented than other more technical oriented ways of working. Fact Oriented Modeling helps you close the gap between business and IT.

Modern data architectures work with the four quadrants of Ronald Damhof, in which one quarter is almost completely defined by Fact Models. It has been applied in the Dutch National Bank, the Tax Department, and now the Department of Justice and Safety in the Netherlands. It supports the vertical data architecture, being the data at rest, from law, regulations, procedures, down to the definitions and implementations in databases.

In general, the path to growth is to realize the business IT gap is real. Once this realization sets it, it is no longer just a new tool which will fix the problem.