Good Practice Award 2020: The Finalists Have Now been Announced
We are happy to announce the three finalists of the year 2020: BAYER AG, Beiersdorf AG, and Deutsche Bank AG. The finalists will present their good practices to the CC CDQ community during the next workshop on December 9th. The winner will then be announced in the evening that same day.
Good Practice Award Finalists
Data Strategy
A Data Strategy defines how a company will manage and use its data to generate value. We explain how to build a strategy and why it is essential for your business.
Data Strategy
CC CDQ Continues Working as Virtual Community!
Due to the current Corona pandemic, we now support our community members remotely. Information about our workshops, co-innovation and focus group activities.
CC CDQ goes virtual
Recent Publications
Our various publications create added value for you and your company. Scientifically based models and methods for efficient management of your data.
Request publications for free
Managing Enterprise Analytics Platforms
Successful management of enterprise analytics platforms requires scalable data onboarding and analytics delivery processes with little human intervention but strong governance.
Managing Enterprise Analytics Platforms
Using Machine Learning for Improving Data Quality
Increased data volumes put companies under pressure to systematically manage and control their data assets. Find out how Artificial Intelligence (AI) and Machine Learning (ML) techniques can support you in your data management activities.
Machine Learning
Data Excellence Model (DXM)
The digital transformation of businesses has brought about a fundamental change in many industries. The new Data Excellence Model offers support and guidance for practitioners.
Data Excellence Model
Open Data App Store
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
Data Catalog Reference Model and Market Study published
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 Catalogs
We are hiring: PhD students
We invite applications for our PhD Positions (100%) at the University of Lausanne/HEC in the Competence Center Corporate Data Quality. You will contribute to the design and implementation of a Data App Store or Machine Learning interrogations in business contexts. Employment rate is 100%!
To our PhD job offers
Competence Center Corporate Data Quality (CC CDQ)
Bridging the gap between theory and practice by bringing together data management experts from companies and academia
The Competence Center Corporate Data Quality (CC CDQ) is a data management research consortium and expert community addressing the challenges resulting from digitalization and data-driven strategies. The core objective of the CC CDQ is to transfer innovative concepts and scientific research results in the domain of data management to everyday business practice in order to support companies in managing data as an asset.
- Corporate partners are more than 15 renowned companies from different industries that consider data management critical for the success of their business.
- Researchers come from leading academic institutions – among them the Faculty of Business and Economics (HEC – University of Lausanne), the Institute of Information Management (IWI – University of St. Gallen), and the Institute of Accounting, Control and Auditing (ACA – University of St. Gallen).
The CC CDQ is headed by Prof. Dr. Christine Legner (HEC – University of Lausanne) and operated by CDQ AG
Based on latest scientific and practical insights, the CC CDQ develops methods, architectures, reference models, and prototypes needed for efficient implementation of data management. As an expert community, the CC CDQ hosts workshops and focus groups in which knowledge and experiences are shared, best practices are presented, and approaches and solutions are discussed.
Good Practice Award 2020: The Finalists Have Now been Announced
Bayer, Beiersdorf, and Deutsche Bank made it into the final round of this year's award.
Webinar Series: How to Manage Data as an Asset
This webinar series summarizes good practices and research results of the Competence Center Corporate Data Quality (CC CDQ).
Success Story: Data Management at Schaeffler
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 CC CDQ.
CC CDQ Continues Working as Virtual Community!
Due to the current Corona pandemic, we now support our community members remotely. Here you can find information about our workshops, co-innovation and focus group activities.
Data Strategy Canvas
Defining the Building Blocks of a Data Strategy
Request document
Data Documentation for Data Catalogs: Metadata model and attributes (Work report, 2020)
Data Excellence Model Template (2019)
Managing Data as an Asset with the Help of Artificial Intelligence (Study, 2019)
Webinar Recording: The Data Excellence Model
In this webinar, Prof. Dr. Christine Legner (University of Lausanne) and Tobias Pentek (CC CDQ) explain how you can assess, develop, and improve your data management activities using the CDQ Data Excellence Model.
Length: 44 minutes
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
Data sharing for better data quality
CDQ's innovative data sharing solutions ensure better data quality of customer and vendor master data with less manual effort. Taking a first step is easy! Data sharing for better data quality
Data Quality Solutions
CDQ's innovative Data Quality Solutions help you to improve your customer and supplier master data in three stages, saving time and costs at the same time. Getting started is easy! Improve your data quality now!
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 9008 St. Gallen
Switzerland
88045 Friedrichshafen
Germany
