Remediation
Remediation in data science refers to the process of identifying and correcting errors or inconsistencies in data. It involves the use of various techniques such as data cleaning, data transformation, and data normalization to ensure that the data is accurate, complete, and consistent. Remediation is an important step in the data analysis process as it helps to improve the quality of the data and ensure that the results of the analysis are reliable and accurate. In addition, remediation can also involve the use of machine learning algorithms to automatically identify and correct errors in the data.
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