Data cleansing is the process by which data is cleansed and improved so that the data quality
goes up. Sometimes data cleansing is also called data cleaning or data scrubbing. It is often part of an ETLordata wrangling process. All have the same goal of putting the familiar phrase “Garbage in, Garbage out” out the door for good.
For example, in the context of data analytics, data cleansing can be used to detect and correct errors or incomplete data, to remove duplicates, and to standardize data so that it can be used consistently in analyses.
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