Data Cleansing, also known as data scrubbing or data cleaning, is the process of identifying and rectifying errors, inconsistencies, inaccuracies, and redundancies in a dataset. The goal of data cleansing is to improve data quality and reliability by ensuring that the data is accurate, complete, consistent, and up-to-date.
Data Cleansing is a critical process that ensures data accuracy, consistency, and reliability by identifying and rectifying errors and inaccuracies. It improves the quality of data, leading to better decision-making, efficient operations, and improved customer experiences.
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