Description: The transformation function is a specific operation that alters data in a defined way, allowing it to be suitable for further analysis. In the context of data preprocessing and ETL (Extract, Transform, Load), this function is crucial for converting raw data into a more useful and understandable format. Transformations can include data normalization, type conversion, information aggregation, cleaning erroneous or duplicate data, and creating new variables from existing ones. This process not only improves data quality but also facilitates its integration into analysis and decision-making systems. The transformation function can be implemented using various tools and programming languages, such as SQL, Python, or R, and is an essential component in preparing data for machine learning and business intelligence. In summary, the transformation function is a fundamental step in the data lifecycle, ensuring that information is accurate, relevant, and ready for advanced analysis.
