Data transformation is crucial because raw data is often incomplete, inconsistent, or collected from various sources that may not be directly comparable. Transforming this data helps to:
Improve Data Quality: Cleaning data by correcting errors, removing duplicates, and handling missing values. Enable Comparability: Normalizing data to ensure it can be compared across different populations or time periods. Facilitate Analysis: Aggregating data to make it more manageable and suitable for statistical analysis.
