The purpose of this study is to identify issues associated with cleaning computerized data files, using the example of large-scale data collection activities conducted by the Bureau of Labor Statistics (BLS). This paper will describe data editing activities and processes currently implemented to clean data collected by BLS through CAPI and CATI interviews. Similarities and differences in current data editing procedures are described, as well as common and unique decision rules used by the various BLS surveys in the conduct of both household and establishment surveys. This study describes features associated with data editing software systems in place at the BLS; identifies data editing issues shared in common among BLS surveys; and documents the types of data editing activities and procedures currently implemented at the BLS, as well as how these procedures address data editing needs. This integrated profile is designed to provide an overview of major data editing activities conducted by the BLS to improve data quality that can enhance and inform data reporting.