Data cleansing is the process of identifying and correcting errors or inconsistencies in data to improve its quality. This involves removing duplicate entries, fixing typos, and ensuring that data is formatted correctly. Clean data is essential for accurate analysis and decision-making. The importance of data cleansing extends to various fields, including business analytics, healthcare, and research. By maintaining high-quality data, organizations can enhance their operations, improve customer satisfaction, and make informed decisions based on reliable information. Effective data cleansing helps prevent costly mistakes and supports better outcomes.