How to address the shortcomings of shallow and outdated models and future-proof your modeling strategy
I have been working in data modeling for over 30 years, creating a variety of data models (3NF, dimensional, set (anchor, data vault), graphs, etc.) mostly for analytical systems. However, many of them have also become obsolete or outdated. Sometimes it seems like the work of the unfortunate Sisyphus who insistently rolls his stone up a hill, only to realize at some point that it was in vain again.
For a long time, I was convinced that it was necessary to create a centralized model of a common and comprehensive view of a company's business affairs. After all, entrepreneurs who have been involved in the modeling process for a long time know what is going on in the company, don't they? Well, the smaller the company, the closer it was to achieving the goal. But to be completely honest, in the end each model remained a mere approximation, a static view that tried to reflect the constantly changing reality.
But even though creating such a model is quite laborious, we cannot succeed without it. The modern data-driven enterprise is built on the core idea of extracting value from data. However, the fact is that data has no value in itself. We need to use…
