Data Science Use Cases
Speaker: Ralf Klinkenberg, Co-Founder and Head of Data Science Research at RapidMiner.
The talk addressed industrial applications of data science, framed around the CRISP-DM methodology, and discussed how such approaches are applied to real-world business problems.
Focus Areas
- CRISP-DM as a structured approach to data mining projects.
- Industrial use cases illustrating applied data science in practice.
- Perspectives from RapidMiner on bridging research and industry applications.
Industry-focused sessions at ICIT 2017 are designed to bring together researchers, developers, and practitioners from academia and industry to exchange findings on applied technology. The programme features invited talks that frame methodologies in practical terms, helping participants connect theoretical tracks with real-world implementation. By blending technical depth with industrial relevance, the conference creates a forum where quality research meets the demands of contemporary engineering practice, supporting a productive dialogue between those who build systems and those who study them.
One such contribution highlights data science use cases, drawing on a structured methodology for mining projects and presenting industrial applications drawn from business settings. The session explores how organizations move from raw data to actionable insight, offering perspectives on bridging research with operational deployment. Attendees are encouraged to extend the discussion through related tutorials that provide hands-on exposure, reinforcing the conference commitment to learning that spans both scholarly inquiry and industrial application.
Related
Participants interested in hands-on sessions can also refer to the conference Tutorials page, covering related topics in machine learning and data science.