Learn in the textbookData Analysis and Preprocessing
DefinitionData cleansing (データクレンジング) is the work of finding and correcting errors and inconsistencies in collected data to raise data quality.
ExplanationTypical flaws include typing errors, duplicates where the same thing is registered twice, inconsistent notation where the same content is written in different ways, and missing values where a field is empty. If you aggregate or join data with these flaws still in it, one person may be counted as two, and the results can no longer be trusted. That is why cleansing is done before the data is used for analysis or storage.
AnalogyIt is like tidying your address book before sending holiday cards. If a friend appears twice, under an old and a new surname, you merge the entries, and you update the addresses of people who have moved before printing the labels.
Memory hookCleanse means to wash thoroughly, the same word as in a facial cleanser. Picture scrubbing the dirt off your data.