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CC CDQ Steering Committee - online
November 5 2026
#95 CC CDQ Workshop + CDQ Good Practice Award- Berlin
November 25-26 2026
#37 CDQ's SAP Focus Group Workshop
December 3 2026
Latest uploaded documents
| Title | Type, Company presentation, Break-out sessions, Co-Innovation | Upload date | |
|---|---|---|---|
| Reality Constructed, Reality Lost: Navigating Multiple Digital Realities of Sustainability | Scientific publication | Reality Constructed, Reality Lost Navigating Multiple Digital Realities of Sustainability.pdf | |
| Managing Sustainability Data Proactively: Corporate Sustainability Reporting (Directive) as a Driver | Scientific publication | Managing Sustainability Data Proactively - Corporate Sustainability Reporting (Directive) as a Driver ISJ 2026.pdf | |
| The Medium is the Prompt: Prompts as Design Science Artifacts | Scientific publication | The Medium is the Prompt - Prompts as Design Science Artifacts DESRIST 2026.pdf | |
| Cogito, Ergo Prompt: Understanding how LLMs can Support Data Work | Scientific publication | Cogito, Ergo Prompt - Understanding how LLMs can Support Data Work WI 2026.pdf | |
| Game of Frames: AI-Enabled Metadata Generation in Enterprise Video Archives | Scientific publication | Game of Frames - AI-Enabled Metadata Generation in Enterprise Video Archives WI 2026.pdf |
Latest workshop
Latest research briefings
Research Briefings provide concise, 3–4-page management summaries of key CC CDQ research topics.
CC Research Topics
Agentic AI & GenAI for Data Management
Agentic AI and generative AI offer new opportunities to redesign data management workflows and delegate complex tasks to AI agents. However, organizations still need to determine which tasks are suitable for delegation and how agentic systems can be implemented safely and effectively. This co-innovation explores and creates agentic AI reference architectures for data management, key application areas, agent interaction maps, risk assessment, and governance principles.
Unstructured Data & Semantic Layer
Organizations generate vast volumes of unstructured data, yet much of this information remains difficult to access, manage, and reuse. Recent advances in generative AI create new opportunities to leverage documents, messages, images, and other unstructured sources, but their success depends on reliable data preparation and meaningful context. This co-innovation explores and creates use case archetypes, data preparation blueprints, data readiness checklist, a metadata model, and reference models for semantic layers and unstructured data management.