Today, access to valuable data is a superpower. But just having a lot of data is not enough. In our recent e-book, our experts explain how to turn data into business value using a simple model – the Data Value Formula.
The Data Value Formula
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
In 2020, Bayer, Beiersdorf, and Deutsche Bank made it to the final round of the CDQ Good Practice Award. We are happy to announce the winner and finalists of the competition and their innovative submissions.
Winner & Finalists
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
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
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
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
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
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 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
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.
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.
We are happy to announce the winner and finalists of the competition and their innovative submissions.
Bayer, Beiersdorf, and Deutsche Bank made it into the final round of this year's award.
This webinar series summarizes good practices and research results of the Competence Center Corporate Data Quality (CC CDQ).
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.
Three keys to unlock your data's full potential.
Request documentDefining the Building Blocks of a Data Strategy
Request documentIn 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