"In every company, there is invariably the one word or phrase that is critical to the business the company is in. This in the word that everyone uses.Data modeling is hard, it's hard to agree on what exactly it is that needs to be modeled. IT solutions are supposed to mirror the needs of 'the business', but there are lots of different components of a business.
The problem is that no one can define it. Or rather everyone defines it. There is no single definition.
Don't include that word in your model. Instead, for each of the concepts represented, find a clear term to describe that concept."
--David Hay
Hay provides an example: In an oil refinery he modeled, the word everyone used--in different ways--was 'stream.' So, instead, he chose 'fluid path', 'material assignment,' and 'movement.'
There's nothing special about oil refineries or any other type of business. Nor is the problem of ambiguity specific to data modelers. But it sure makes our job hard. Coming to a single definition on a term can bring out all the factional politics that you hoped you could avoid by being a technology professional.
One very important way of getting everyone on the same page is defining shared terms, as Hay suggests, and then circulating these terms so that everyone uses them. But it may turn out that different people or groups want to see the same information in multiple ways, or only care about it at different levels of granularity.
It is likely that you will be able to come to agreement, since you all are part of the same business. Still, the world can be described correctly in many ways. For thousands of years, philosophers have sought to model the essential nature of reality, but they could never agree. Is the world dominated by change or permanence, progress or cycles, one thing or many?
A data model or a metaphysics is a map. Any map will show certain things and not others. It represents only those things we are interested in. If it were truly accurate, it would have to be the same size as the world, as Borges jokes in a short passage. Similarly, all data models have their uses. Make sure it's clear what uses your model serves.
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