Data cleansing is the process of correcting or removing inaccuracies and inconsistencies in datasets. It improves data quality by ensuring that information is accurate, complete, and reliable. By eliminating duplicate entries, correcting errors, and filling in missing values, organizations can enhance the integrity of their data. This process is essential for effective data analysis, as high-quality data leads to better decision-making and more reliable business insights. Ultimately, improved data quality contributes to operational efficiency and strategic initiatives.