Data Management Research

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).

Latest Data Management Research Activities

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:

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.

CDQ Data Excellence Model (DXM)

The Data Excellence Model offers support and guidance for practitioners in the implementation of data management by defining major design areas, while at the same time supporting the transformation into a digital and data-driven company. The CDQ Data Excellence Model

Managing Enterprise Analytics Platforms

Successful management of Managing Enterprise Analytics Platforms requires scalable data onboarding and analytics delivery processes with little human intervention but strong governance. Managing Enterprise Analytics Platforms

Sourcing and Managing External Data

Despite 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

Data Management for Data Protection (GDPR)

The CC CDQ research team provides a data-centric view on data protection regulatory requirements throughout the data lifecycle. Data Management for Data Protection

Data Catalog

The Competence Center Corporate Data Quality (CC CDQ), in collaboration with researchers from Fraunhofer ISST and many data management experts, developed a data catalog reference model and a market study. Data Catalog Reference Model & Market Study

Data Strategy

A data strategy defines how a company will manage and use its data to generate value. We explain how to build a data strategy and why it is essential for business. Data Strategy to Manage Data Successfully

Data Valuation

How much is your company’s data worth? Determining the economic value of data is a prerequisite for effectively managing data - and a very challenging task. This topic has been in the focus of the CC CDQ’s research activities for some years now. Data Valuation

Open Data App Store for Business

The Competence Center Corporate Data Quality (CC CDQ), together with the University of Lausanne, launched a project to provide an "Open Data App Store" that supports businesses in finding, integrating and using open data. Open Data App Store

Machine Learning for Improving Data Quality

Increased data volumes put companies under pressure to systematically manage their data assets. Learn how Artificial Intelligence (AI) and Machine Learning (ML) techniques can improve your data quality. Machine Learning for Improving Data Quality

Data Retention

Our Sharing Economy approach to data retention helps companies comply with the growing number of legal and business data archiving requirements. Data Retention on Master Data

Data Governance

What is data governance, how can it be implemented in the company and what are the benefits of strong data governance? Our data management experts provide the answers and valuable insights. Data Governance

Our Awards

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.

Good Practice Award

The CDQ Good Practice Award acknowledges outstanding, innovative projects in the field of data management. The practices submitted are evaluated by an international jury of data management experts and by the member organizations of the CC CDQ. CDQ Good Practice Award

Data Management Services

Whether data quality analytics, address validation, deduplication or bank account verification: CDQ's innovative data management services help you to enhance the quality of your vendor and customer master data. Data Management Services

Success Story: Data Management at Schaeffler Group

In an article recently published in the specialist magazine "Big Data Insider", Markus Rahm provides insights into data management at Schaeffler. And how it has evolved with the help of the CC CDQ. Data Management at the Schaeffler Group
Go to top