Perspective on Performance Optimisation and Data Quality
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This might come as a surprise for some people: data modelling is often a collaborative effort, involving lively debates with people from various fields. It’s a typical breeding ground for whimsical ideas and clever tricks, making it a classic subject for debate on the best approach. To make the topic a little more dramatic, I like to think of it as a battle between the gray-bearded purist with a thick handbook of rules and the impetuous avant-gardist who simply throws fancy NoSQL (whatever this means) at everything.
Having a set of rules is helpful because it’s hard to understand all the effects of decisions, especially when facing a new problem. Experience plays a crucial role in mastering any discipline, data modelling is no different. Established rules and conventions serve as an essential framework to bridge the knowledge gap. Yet, there is a nuanced balance between adhering to these guidelines and being open to experience and pragmatic reasoning.
“Know the rules well, so you can break them effectively.”
Dalai Lama’s 18 Rules for Living
In my opinion, this adage really nails it. I value making educated decisions, and while reasoning with conventional rules…