What term refers to the entire process of preparing and transforming data into a usable form?

The term that refers to the entire process of preparing and transforming data into a usable form is data wrangling. This process encompasses a variety of tasks, including data cleaning, data transformation, and data integration, ensuring that raw data is appropriately processed and ready for analysis or machine learning applications.

Data wrangling involves identifying, acquiring, and structuring data from various sources, which may include cleaning inaccuracies, handling missing values, and converting data into formats suitable for analysis. This comprehensive approach is essential, as it allows practitioners to derive meaningful insights and build robust models based on clean and well-structured data.

While feature engineering focuses specifically on creating new features or modifying existing ones to improve model performance, and dimensionality reduction involves simplifying data sets by reducing the number of features while preserving essential information, these are only parts of the overall data preparation process. Data cleaning, on the other hand, is a crucial step within data wrangling, but it doesn't encompass the full range of activities involved in preparing data for analysis. Thus, data wrangling is the most appropriate term for the entire process.