Innovative data management concepts, methods and tools based on academic research
The research outcomes of the Competence Center Corporate Data Quality (CC CDQ) are the result of co-innovation by research institutions and companies. Typical research results are e.g. reference models, architectures, methods or case studies which can be directly implemented by the partner companies of the CC CDQ community to improve their data management in everyday practice. A key result of CC CDQ research is the Data Excellence Model, which provides practitioners with support and guidance in the implementation of data management.
The current research activities extend the established CC CDQ data management concepts to address digitalization, big data and advanced analytics as well as regulatory compliance:
- Data catalogs: approaches, implementation and adoption
- Managing Big Data & Analytics
- Data quality and business impact
- SAP MDG exchange
- Data strategies
- AI and new technologies in data management
Current topics from the area of Data Management Research
Here you will find a selection of our current research and best practice topics, which we develop and advance together with our members.
Machine Learning for Improving Data QualityIncreased data volumes put companies under pressure to systematically manage and control their data assets. Learn how Artificial Intelligence (AI) and Machine Learning (ML) techniques can support and improve your data quality. Using Machine Learning for Improving Data Quality
With our annual awards, we honor outstanding achievements in the field of data and data quality management. While the Young Talent Award is aimed at students from universities in Germany, Switzerland, Austria, or Liechtenstein, the Good Practice Award is open to all companies that are interested in improvements in the field of data management.
The judging juries are made up of top-class data management experts from industry and science.