Most of math is basically 'build a machine that behaves like our observations or intuition' (depending on if you're doing applied or pure math, respectively)^. The 'machine' is abstract, not literal, and is usually called the 'model' of the process we observe or intuit and want to simulate.
In this understanding, the nearest analog is the Lego Set. Every Lego set is made up of many bricks and parts, some bricks behave in different ways to one another (e.g., in Automata Theory you'll have a lot of production-rule 'bricks', but in Stats you'll have a lot of formulae and special variables, and in Trig you have a lot of identities -- all bricks, different flavors). As you build a new model out of bricks, you may need to borrow from other sets to help make part of your new machine work. Simple machines can be deep and complex if you use the right bricks, and big and complicated machines can be understood as a collection of simpler parts. The model, ultimately, is like the Lego model on the front of the box, it's your goal, but it's not any one part of the set, it's the sum of all the parts.
 Don't @ me Pure math people.