A data transformation is a function that is applied to some input data that changes the data in such a way that the data is easier to consume by downstream applications or users (often business intelligence or ML). Data transformations can take many forms, from simple operations such as filtering or sorting, to complex algorithms such as grouped aggregations, binning, dimensionality reduction, or data cleaning.
Data transformations are important because they allow raw data to be cleaned, processed, and standardized, making it easier to work with and analyze. By transforming data into a format that is compatible with downstream applications and systems, data transformations can help improve the accuracy and efficiency of machine learning models and other data-driven applications.