Data cleaning is the process of identifying, correcting, modifying, or removing inaccurate, incomplete, duplicate, inconsistent, and irrelevant data from a dataset to improve its quality, accuracy, and reliability.
It involves checking data for errors, handling missing values, removing duplicate records, correcting spelling and formatting mistakes, standardizing data entries, and ensuring consistency across the dataset.... Read more