Necessary activities that need to be performed on data to get the data ready to be used for an analytics or machine learning project. Data preparation includes aspects of data cleaning, data transformation, data wrangling, data augmentation, anonymization, and other actions to be performed on data, usually as part of a data engineering data pipeline.