Data Cleansing

Data Cleansing detects and corrects disparities and errors within a data set. By cleansing data, users can catch and correct incomplete, incorrect, or duplicate records and elements to make their data more usable. This process catches common mistakes like mistyped or misheard information, missing or default values, out-of-date information, non-standardized formatting, and incomplete data capture. Data Cleansing is beneficial because it ensures better consistency in data sets and preserves the overall quality of collected data.