Data cleansing is a critical issue in business because inaccurate, outdated, or inconsistent data can significantly infect decision-making and operational efficiency. Poor data quality leads to errors, reduced productivity, and misguided strategies, costing businesses both time and money. Ensuring data integrity involves removing duplicates, correcting errors, and standardizing formats, which can be labour-intensive and complex. Moreover, as businesses collect data from diverse sources, the risk of inconsistencies and inaccuracies increases. Effective data cleansing enhances the reliability of data-driven insights, supports compliance with regulatory standards, and improves customer satisfaction by ensuring accurate information. By addressing data quality issues, businesses can make more informed decisions, streamline operations, and gain a competitive edge. Consequently, investing in robust data cleansing for a business is essential for maintaining data accuracy and maximizing the value of business intelligence.