Home
Final CC CDQ web session: Co-Innovation: AI for data management
November 20, 2025
• • •
Final CC CDQ web session: Co-Innovation: Data foundations for analytics and AI
December 9, 2025
• • •
Latest uploaded documents
| Title | Type, Company presentation, Break-out sessions, Co-Innovation | Upload date | |
|---|---|---|---|
| 33rd CDQ SAP MDG WS September 2025 - Meeting Minutes | SAP MDG Focus Group | 6 October 2025 | 33rd CDQ SAP MDG WS September 2025 - Meeting Minutes.pdf |
| (05) CC CDQ WS 90 BoS EU Data Act_Elizabeth Teracino_Jingyang Wang_UNIL | Breakout session | 1 October 2025 | (05) CC CDQ WS 90 BoS EU Data Act Elizabeth Teracino Jingyang Wang UNIL.pdf |
| (04) CC CDQ WS 90 Guardrails for acceptable data use in the age of AI_Barbara Wixom_MIT | Company presentation | 30 September 2025 | (04) CC CDQ WS 90 Guardrails for acceptable data use in the age of AI Barbara Wixom MIT.pdf |
| (07) CC CDQ WS 90 BoS Acceptable Data Use_Barbara Wixom_MIT_Hippolyte Lefebvre_UNIL | Breakout session | 29 September 2025 | (07) CC CDQ WS 90 BoS Acceptable Data Use Barbara Wixom MIT Hippolyte Lefebvre UNIL.pdf |
| (06) CC CDQ WS 90 BoS Data Management_Enterprise Architecture_Christine Legner, Tilman Friedrich_UNIL | Breakout session | 29 September 2025 | (06) CC CDQ WS 90 BoS Data Management Enterprise Architecture Christine Legner, Tilman Friedrich UNIL.pdf |
Latest workshop
| Title | Upload date | |
|---|---|---|
| (01) CC CDQ WS 90 Introduction_Christine Legner_UNIL_Tobias Pentek_Richard Lehmann_CDQ | 25 September 2025 | (01) CC CDQ WS 90 Introduction Christine Legner UNIL Tobias Pentek Richard Lehmann CDQ.pdf |
| (02) CC CDQ WS 90 EU Data Act as a driver for data collaboration and monetization_Dominik Ebeling_Rolls Royce Power System | 25 September 2025 | (02) CC CDQ WS 90 EU Data Act as a driver for data collaboration and monetization Dominik Ebeling Rolls Royce Power System.pdf |
| (03) CC CDQ WS 90 Journey towards data products at enterprise scale_Redwan_Hasan_UNIL | 25 September 2025 | (03) CC CDQ WS 90 Journey towards data products at enterprise scale Redwan Hasan UNIL.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.