The best way to address the shortcomings of shallow, outdated models and future-proof your modeling strategy
I even have been involved in modeling data for over 30 years, creating a wide range of data models (3NF, dimensional, ensemble (anchor, data-vault), graphs, etc.) mainly for analytical systems. Nevertheless, lots of these have also step by step change into outdated or obsolete. Sometimes it looks like the work of the unlucky Sisyphus who persistently rolls his boulder up the hill, only to understand sooner or later that it was in vain again.
For a really very long time, I used to be convinced that it should be possible to centrally model a standard and complete view of business matters for a corporation. In spite of everything, long-time business individuals who have been involved within the modeling process know what’s happening in the corporate, right? Well, the smaller the corporate was, the closer I reached the goal. But to be completely honest, ultimately, each model remained just an approximation — a static view that attempted to reflect the continuously changing reality.
But even when it is sort of laborious to create such a model, we absolutely cannot achieve success without it. The trendy data-driven enterprise is predicated on the core idea of deriving value from data. Nevertheless, the very fact is that data has no value in and of itself. We’d like to make use of…
