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Noisy data are data that is corrupted, distorted, or has a low signal-to-noise ratio. Improper procedures (or improperly-documented procedures) to subtract out the noise in data can lead to a false sense of accuracy or false conclusions.
Noisy data are data with a large amount of additional meaningless information in it called noise.[1] This includes data corruption and the term is often used as a synonym for corrupt data.[1] It also includes any data that a user system cannot understand and interpret correctly. Many systems, for example, cannot use unstructured text. Noisy data can adversely affect the results of any data analysis and skew conclusions if not handled properly. Statistical analysis is sometimes used to weed the noise out of noisy data.[1]