Cleanedup

Cleanedup is a term used in information management and data processing to describe data, artifacts, or outputs that have undergone cleaning to remove errors, inconsistencies, and redundancies. A cleanedup dataset typically has undergone validation, standardization of formats, handling of missing values, deduplication, and normalization to support reliable analysis and interoperability.

In practice, cleanedup serves as a label rather than a formal standard. It appears in documentation and pipelines to indicate that a stage has finished processing and the resulting artifact is ready for downstream use. The specifics of what constitutes "cleaned up" can vary by project, language, and domain, but common operations include removing invalid records, correcting typos, conforming field lengths and data types, and ensuring consistent encoding.

There is no widely recognized product, organization, or protocol officially named Cleanedup as of the present, and if a project adopts the name, it is typically a minor or internal tool rather than a widely cited standard. When encountered, cleanedup is usually understood as a shorthand for something that has undergone data cleaning or artifact preparation.

See also: data cleaning, data wrangling, data normalization, deduplication, ETL.