'Data cleansing' in data management refers to the process of identifying and correcting inaccuracies or inconsistencies in data to improve its quality and reliability. This essential step involves removing duplicate entries, filling in missing values, and correcting errors in datasets. By ensuring that the data is accurate, consistent, and up-to-date, organizations can make informed decisions based on trustworthy information. Data cleansing is critical for maintaining the integrity of data analysis and reporting, allowing organizations to derive valuable insights effectively. Overall, effective data cleansing enhances the usability and value of data in various applications.