Preprocessing is vital because raw data can be noisy, incomplete, or inconsistent. Proper preprocessing helps address these issues, enhancing the data quality and ensuring that subsequent analyses yield valid and reliable results. It also makes it easier to integrate data from multiple sources, which is often necessary in epidemiological studies.
