The process of converting data from one format, structure, or value set into another.
Data transformation is a core step in any data pipeline. It may involve changing data types, renaming fields, splitting or merging columns, converting units, standardizing codes, or aggregating values. The goal is to make data consistent and usable for its intended purpose.
Example: A dataset from one province records dates as DD/MM/YYYY while another uses YYYY-MM-DD. A transformation step converts both to ISO 8601 format before the datasets are merged for national analysis.
Transformation is the "T" in ETL (Extract, Transform, Load). Without it, data from different sources cannot be reliably combined or compared.