Web Reference: Feb 7, 2026 · Data cleaning is the process of preparing raw data by detecting and correcting errors so it can be effectively used for analysis. It is a foundational step in data preprocessing that ensures datasets are suitable for analytical, statistical and machine learning tasks. Data cleaning is the process of fixing or removing incorrect, corrupted, incorrectly formatted, duplicate, or incomplete data within a dataset. When combining multiple data sources, there are many opportunities for data to be duplicated or mislabeled. Data cleaning, also called data cleansing or data scrubbing, is the process of identifying and correcting errors and inconsistencies in raw data sets to improve data quality.
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