Data Quality Management Procedures are specific guidelines, routines, and mechanisms designed to implement, rectify, and maintain stringent data quality management protocols. These procedures encompass activities such as profiling, measuring, monitoring, cleansing, and validating data against established quality metrics. By addressing dimensions like accuracy, completeness, and timeliness, they ensure data aligns with organizational goals, supports decision-making, and fosters continuous improvement through consistent and reliable data practices.