Free Webinar Series: How to Manage Data as an Asset

During our free webinar series, we will explain how to assess, develop and improve your data management activities using the Data Excellence Model, why a data strategy is key to transforming into a data-driven organization, and how to organize data assets with a data catalog.
Register now for free!

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

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

Get in touch with us

We look forward to your message!

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.

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

03.07.2020

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).

17.04.2020

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.

26.03.2020

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.

23.03.2020

Empowering Data Consumers to Work with Data: Data Documentation

 The CC CDQ metadata reference model for data documentation in the enterprise context  was developed with CC CDQ member following a Design Science Research process.

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Publications

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 Management Services

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

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
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