Data Management for Data Protection (GDPR)

Data protection regulations, such as GDPR, are fundamentally about data management. The CC CDQ research team provides a data-centric view on data protection regulatory requirements throughout the data lifecycle.
Data Management for Data Protection

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

Managing Big Data & Analytics

Successful management of Big Data and Analytics requires scalable data onboarding and analytics delivery processes with little human intervention but strong governance.
Big Data & Analytics

Recent Publications

Our various publications create added value for you and your company. Scientifically based models and methods for efficient management of your data.
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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

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

Get in touch with us

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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 research consortium and expert community in the field of data management 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.

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News

14.10.2019

Swarovski Group joined the Competence Center Corporate Data Quality

We'll give you a quick overview of how our latest community member's data management currently looks like.

11.10.2019

CDQ Young Talent Award: Looking for the Winner 2019

Now we are looking for the winner for 2019. Deadline for submission for the 2019 CDQ Young Talent award is January 15, 2020.

10.10.2019

Four Valuable Recommendations to Improve Data Quality

Key takeaways from the focus group "Data Quality for Business Impact" to improve the quality of your data.

09.10.2019

Whitepaper "Managing Data as an Asset with the Help of AI" available now!

Researches from the Competence Center Corporate Data Quality (CC CDQ) have been looking into how businesses can derive value from the rapid growth in data.

08.10.2019

CDQ Good Practice Award 2019: Tough Decision for the Jury

All good practice description submitted are currently evaluated by at least three members of the international jury. Here you can get a first overview of participating companies and title of their submission.


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
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