Innovative Data Management Concepts, Methods and Tools Based on Academic Research
The data management 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's data management research is the Data Excellence Model, which provides practitioners with support and guidance in the implementation of data management.
Our data management researchers come from leading academic institutions, such as the Faculty of Economics (HEC - University of Lausanne), the Institute for Information Management (IWI - University of St. Gallen) and the Institute for Accounting, Controlling and Auditing (ACA - University of St. Gallen).
The current data management research activities extend the established CC CDQ concepts to address digitalization, big data and advanced analytics as well as regulatory compliance:
- Data catalogs: approaches, implementation and adoption
- Managing Enterprise Analytics Platforms
- Data quality and business impact
- SAP MDG exchange
- Data strategies
- AI and new technologies in data management
- Data Retention
Current topics from the area of Data Management Research
Here you will find a selection of our current data management research and best practice topics, which we develop and advance together with our members.
Sourcing and Managing External DataDespite its enormous business potential external data often remains an untapped resource. We explain what external data is and what the difference between the 4 types of external data (open data, paid data, shared data, and social media data) are. Sourcing and Managing External Data
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.