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The process of cleaning data involves parsing, correcting, standardizing, matching, and consolidating. Parsing involves identifying individual data elements and isolating them from the source files. Correcting entails fixing errors like misspellings or typos. Standardizing means following a set of formatting rules. Matching involves searching and finding similar data points. Consolidating is combining cleaned data into a single source. Examples include parsing names or addresses and fixing errors like zip codes or misspellings. It is important to standardize data format and match similar information for effective data cleaning.
