Once we create properties, we clearly need some knowledge written in them. Even higher can be to get the right knowledge! 😉 Due to that, we give the labels significant names and specify models, for example, the label “Size [cm]” clearly defines what we’d like there. If any individual fills it with the worth “inexperienced”, we all know one thing is unsuitable. A pc not essentially although. However, for us, it doesn’t matter if the label is full of the worth “three” or “3”. However for a machine it does.

In different phrases, every knowledge level has an attribute that helps to translate software program methods to perceive its worth. This, in flip, enable a pc to carry out an accurate operation on knowledge. Every property in our mannequin has a that means readable to people and machines.

To resolve the 2 aforementioned challenges, machines function on an attribute worth referred to as knowledge kind. If we assign knowledge kind “Numer” to the sector “Size”, then the software program wouldn’t enable us to jot down neither “inexperienced” nor “three”. We’d be compelled to jot down in “3” (or another quantity naturally). That permits later knowledge processing. A pc can not carry out mathematical operations on values “Two” and “Three”, however it positively can on “2” and “3”. And does it manner higher than we do.

Necessary to notice right here – please don’t misunderstand “knowledge sorts” with “knowledge models”. Mass, size, resistance and others can nonetheless have totally different knowledge sorts. This can be a entire totally different time period.

The entire level of choosing and utilizing right knowledge sorts is to power customers getting into knowledge to do that appropriately. To write down “3” the place it needs to be and never “Three”. This would possibly sound a bit imprecise now, however I provides you with particulars and examples in upcoming chapters.