Dirty data

Dirty data, also known as rogue data,[1] are inaccurate, incomplete or inconsistent data, especially in a computer system or database.

[2] Dirty data can contain such mistakes as spelling or punctuation errors, incorrect data associated with a field, incomplete or outdated data, or even data that has been duplicated in the database.

They can be cleaned through a process known as data cleansing.

Following the definition of Gary T. Marx, Professor Emeritus of MIT, dirty data are one among four types of data:[4][5][6]

This database-related article is a stub.