# 1. Decimal Scaling

It functions by converting a number to a decimal point.To normalize the data by this technique, we divide each value of the data by the maximum absolute value of data.

The **formula** below –

**V’** is the new value after applying the decimal scaling

**V** is the respective value of the attribute

**Example**: Suppose a company wants to compare the salaries of the new joiners. Here are the data values:

Employee Name | Salary |

ABC | 10,000 |

XYZ | 25,000 |

PQR | 8,000 |

MNO | 15,000 |

Now, look for the maximum value in the data.

In this case, it is 25,000. Now count the number of digits in this value. In this case, it is ‘5’. So here ‘j’ is equal to 5, i.e 100,000. This means the V (value of the attribute) needs to be divided by 100,000 here.

After applying the zero decimal scaling formula, here are the new values:

Name | Salary | Salary after Decimal Scaling |

ABC | 10,000 | 0.1 |

XYZ | 25, 000 | 0.25 |

PQR | 8, 000 | 0.08 |

MNO | 15,000 | 0.15 |

**Results after After applying the zero decimal scaling formula**

Thus, decimal scaling can tone down big numbers into easy to understand smaller decimal values.

Also, data attributed to different units becomes easy to read and understand once it is converted into smaller decimal values.