Data cleaning is one part of data quality. The aim of Data Quality (DQ) is to have the following:
Data cleaning attempts to fill in missing values, smooth out noise while identifying outliers, and correct inconsistencies in the data. Data cleaning is usually an iterative two-step process consisting of discrepancy detection and data transformation.
The process of data mining contains two steps in most situations. They are as follows: