data mapping is used to map complex data into a single value

the idea is if an object has complet data to process, like (object, value1, value2, value3,value4....), we can mapping (object, value1, value2, value3,value4....) into a single value X, then we process only X to make it faster

here is an use case:

we have two 2D data arrays with 5 columns, the first column is the name of object, the other fours are the differents value of this object

Data ArrayA:

| object | value1 | value2 | value3 | value4 |
| ------ | ------ | ------ | ------ | ------ |
| X | 1 | 2 | 3 | 4 |
| Y | 5 |  6 | 7 | 8 |
| Z | 9 |  10 | 11 | 12 |

Data ArrayB:

| object | value1 | value2 | value3 | value4 |
| ------ | ------ | ------ | ------ | ------ |
| X | 1 | 2 | 3 | 4 |
| Y | 5 |  8 | 7 | 8 |
| Z | 9 |  10 | 192 | 12 |

now we need to compare data array A to data array B to find which object inside A has different value.

without data mapping, we need to compare each object's 4 values, the complexity is O(2^n)

with data mapping:

we map those values:

(X, 1, 2, 3, 4)  ==> 1

(Y, 5, 6, 7, 8)  ==> 2

(Z, 9, 10, 11,12) ==>3

(Y, 5, 8, 7, 8) ==> 4

(Z, 9, 10, 192, 12) ==> 5

Data ArrayA:

| object |
| ------ |
| 1 |
| 2 |
| 3 |

Data ArrayB:

| object |
| ------ |
| 1 |
| 4 |
| 5 |

then compare 1D array is fast, the complexity is O(n)