The Purpose of Data Cleaning and Preparation

In clinical data management, R should not become a hidden place where data are silently altered. The raw export should remain unchanged. Cleaning scripts should make transformations explicit. Query outputs should identify records that require review. Derived datasets should be traceable to raw inputs and scripts. When corrections are needed in an electronic data capture system, the preferred route is usually to correct the source database through the approved query and audit trail workflow, then re-export the corrected data.