Data scrubbing, also known as data cleansing or data cleaning, is the process of reviewing and refining data to ensure its accuracy, consistency, and quality. The primary goal of data scrubbing is to identify and correct errors, inconsistencies, and inaccuracies in datasets, thereby improving the overall integrity of the data. Key activities involved in data scrubbing include: 1. **Identifying Errors**: Detection of errors such as duplicates, incomplete records, typographical mistakes, and inconsistencies within the data.
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