Data cleaning is crucial for maintaining high-quality data, which in turn drives better business decisions and operational efficiency. It involves refining raw data to ensure accuracy, consistency, and usefulness. Poor data quality can cost organizations millions of dollars annually due to missteps and missed opportunities. Clean and accurate data serves as the backbone of successful businesses and is an essential part of the overall data preprocessing process. By cleaning data, businesses can ensure their analytics are built on reliable, high-quality information, leading to better decision-making and more accurate insights.