dataprocessed

Dataprocessed is a term used in data management to describe data that has undergone a sequence of processing steps to become suitable for analysis and reporting. It contrasts with raw data, which has not yet been cleaned or transformed, and with curated data, which has been selected for a specific purpose and documented.

In practice, dataprocessed data results from ETL or ELT workflows that include cleaning (handling missing values and duplicates), normalization and type casting, aggregation, formatting, enrichment (adding derived attributes from external sources), validation, and documentation of provenance. The goal is to improve accuracy, consistency, and usability while preserving essential lineage.

Dataprocessed data is typically accompanied by metadata describing the transformations performed, the responsible team, and data quality metrics. It supports repeatable analysis, governance, and auditability, and it is commonly used for dashboards, reports, and machine learning feature engineering.

Limitations include the possibility of biased outcomes produced during processing, loss of detail, or misalignment with original intent if documentation is incomplete. Users should review data lineage, assumptions, and quality metrics to interpret results correctly.

See also: data cleaning, data transformation, ETL, ELT, data pipeline, data quality, data lineage.