Data cleansing is the process of detecting and correcting (or removing) corrupt or inaccurate records from a dataset, ensuring the data is accurate, complete, and consistent for analysis. It is a critical step in data preparation that enhances data quality and reliability, ultimately improving the outcomes of data-driven decision-making processes.