Data integrity, as the foundation of quality control (QC) in pharmaceutical enterprises, is directly related to the reliability of drug safety and regulatory compliance. This study focuses on the current state of data management in QC laboratories, identifying the risks to data integrity, and analyzing key aspects of data collection, storage, and protection through typical case studies. Furthermore, by optimizing management processes, strengthening personnel training, and introducing advanced technological systems, a comprehensive strategy to enhance data integrity is proposed. The research confirms that the integrated application of various systems and intelligent technical tools such as the laboratory information management system, microbiological information management system, computerized maintenance management system, warehouse management system and laboratory execution system can effectively ensure full-cycle management of samples, reagents, equipment, and testing data. Case studies further validate the practical effectiveness of the proposed data integrity strategies, providing important references for quality control in pharmaceutical QC laboratories. The study indicates that as regulatory requirements continue to rise, data integrity management will evolve towards intelligent and automated approaches, thereby promoting the continuous improvement of the pharmaceutical industry's quality management system.