Which practice is designed to prevent errors in data entry?

The practice designed specifically to prevent errors in data entry is quality control. Quality control involves systematic monitoring and evaluation of the various aspects of a project, process, or service to ensure that standards are being met. In the context of data entry, quality control measures might include creating standardized procedures for data entry, implementing checks and processes to catch and correct errors before the data is finalized, and training personnel on proper data entry techniques. These proactive steps are crucial in maintaining data integrity and minimizing mistakes during the entry process.

Other practices mentioned, while important in the overall data management process, do not focus specifically on preventing data entry errors. For example, quality audits are retrospective reviews that assess the accuracy and reliability of the data already entered. Data validation ensures that the data entered meets specific criteria but does not necessarily focus on preventing errors at the point of entry itself. Quality assessment examines the effectiveness and efficiency of the processes in place but again is not solely about preventing data entry mistakes. Quality control stands out as the practice directly aimed at preventing these types of errors.