Customer-centered business models, global supply chains as well as risk management and compliance place company-wide requirements on the quality of corporate data. Purely reactive measures of data quality management do not meet these requirements. Instead, companies have to preventively ensure data quality, i.e. when collecting and maintaining data in business processes. Preventive quality management of corporate data (Corporate Data Quality Management, CDQM) poses major challenges, especially for large multinational companies with several divisions. Reasons for this are, for example, the separation of data acquisition and data usage and complex business process and application system architectures. The Competence Center Corporate Data Quality (CC CDQ) is a consortium research project. Together with partner companies, researchers develop strategies, methods, reference models, prototypes and architectures for corporate data quality management.

You can find more information about the CC CDQ on the website and from the University of St. Gallen.