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Latest uploaded documents
| Title | Type, Company presentation, Break-out sessions, Co-Innovation | Upload date | |
|---|---|---|---|
| (05) CC CDQ WS 91 Kuehne+Nagel_GenAI for Business Partner Data_Andreas Nohn | CDQ Award presentation | 5 December 2025 | (05) CC CDQ WS 91 Kuehne+Nagel GenAI for Business Partner Data Andreas Nohn).pdf |
| (03) CC CDQ WS 91 Bosch_Tool Suite for Master Data_Mahesh Medidi_Georg Hinselmann_Raghu Devagiri | CDQ Award presentation | 5 December 2025 | (03) CC CDQ WS 91 Bosch Tool Suite for Master Data Mahesh Medidi Georg Hinselmann Raghu Devagiri.pdf |
| (06) CC CDQ WS 91 Merck_Data_Central_Clara Hechler_Marius Wagner | CDQ Award presentation | 5 December 2025 | (06) CC CDQ WS 91 Merck Data Central Clara Hechler Marius Wagner.pdf |
| (04) CC CDQ WS 91 Thyssenkrupp steel_Driving net working capital excellence through data products_Sebastian Lieu_Tim Foeckersperger | CDQ Award presentation | 4 December 2025 | (04) CC CDQ WS 91 Thyssenkrupp steel Driving net working capital excellence through data products Sebastian Lieu Tim Foeckersperger.pdf |
| CC CDQ Websession results wrap up for 2025 Co-innovation - AI4DM Konrad Schulte_UNIL_Richard Lehmann_CDQ | Co-Innovation | 1 December 2025 | CC CDQ Websession results wrap up for 2025 Co-innovation - AI4DM Konrad Schulte UNIL Richard Lehmann CDQ.pdf |
Latest workshop
| Title | Upload date | |
|---|---|---|
| (01) CC CDQ WS 91 Introduction_Christine Legner_UNIL_Richard Lehmann_Tobias Pentek_CDQ | 1 December 2025 | (01) CC CDQ WS 91 Introduction Christine Legner Richard Lehmann Tobias Pentek.pdf |
| (02) CC CDQ WS 91 Co Inno Results_AI for data management_Konrad Schulte_Richard Lehmann | 1 December 2025 | (02) CC CDQ WS 91 Co Inno Results AI for data management Konrad Schulte Richard Lehmann.pdf |
| (03) CC CDQ WS 91 Bosch_Tool Suite for Master Data_Mahesh Medidi_Georg Hinselmann_Raghu Devagiri | 5 December 2025 | (03) CC CDQ WS 91 Bosch Tool Suite for Master Data Mahesh Medidi Georg Hinselmann Raghu Devagiri.pdf |
Webinars & CC-Videos
CC Research Topics
Data products have the potential to increase data access & reuse, improve governance and control on data and ensure rapid delivery of insights across firms. Therefore, this co-innovation aims to lay the foundation by clarifying the concept of data product, along with its different types and example. Furthermore, we provide a reusable template to support data product design and an end-to-end approach to holistically manage data products. Currently, we are expanding our view from managing single products to portfolio of data products and while doing so, exploring the topic of data product valuation and data product sharing across multiple scenarios.
At the heart of digital transformation is the potential of AI to redefine data management. Therefore, this co-innovation aims to identify the specific impact of AI on current data management practices. Furthermore, when training their own customized AI models, companies often face two problems: they do not have the vast amounts of data necessary to create a competitive AI model and the available data is of inferior quality (heavily lowering a model’s performance). To address the latter problem, we will explore state-of-the-art (AI) techniques to achieve high data quality. We will approach the problem of insufficient data by testing new collaborative approaches for AI projects.
Increasing emphasis on sustainability alongside with stricter regulations and shifting consumer preferences put mounting pressure on enterprises and their largely ad-hoc sustainability activities. This co-innovations group’s research activities focus on developing a scalable approach to address the increasing number of sustainability scenarios. For this goal, the group extensively works on identifying and documenting typical sustainability scenarios, understanding the underlying data requirements, formulating common definitions for sustainability-related data objects, and developing the necessary data management capabilities.
Data quality practices have traditionally focused onto master data. However, with the advent of new technologies, devices and online platforms, these practices need to be extended into other types of data such as observational data, media data and analytical data. In this Co-Innovation group, we 'revisit' data quality in this broaden context and extend to CDQ body of knowledge.