Welcome to IDS 2017 and Overview of Data Science Use Case Presentations

Speaker: Ralf Klinkenberg, RapidMiner

Welcome to the first Industrial Data Science (IDS 2017) conference in the name of the whole organization team. After a short description of the state, challenges, barriers, use cases, and opportunities of Industrial Data Science and of the CRoss- Industry Standard Process for Data Mining (CRISP-DM), which is used as a redline through this event, we provide a short overview over the data science use cases presented at IDS 2017, whose presentation order reflects the steps in CRISP-DM. IDS 2017 focuses on industrial data science applications and best practices, i.e. hands-on experience how to best use data to solve problems in industry and to leverage opportunities. Learn from and discuss with industry experts.

Ralf Klinkenberg

Co-Founder & Head of Data Science Research, RapidMiner

Ralf Klinkenberg, co-founder of and head of data science research at RapidMiner and initiator and co-organizer of the Industrial Data Science Conference, is a data-driven entrepreneur with more than 20 years of experience in machine learning and advanced data analytics research, software development, consulting, and applications in the automotive, aviation, chemical, finance, healthcare, insurance, internet, manufacturing, pharmaceutical, retail, software, and telecom industries. In 2001 he initiated the open source data mining software project RapidMiner with Dr. Ingo Mierswa and Dr. Simon Fischer and in 2007 he founded the predictive analytics software company RapidMiner with Dr. Ingo Mierswa. In 2008 he won the European Open Source Business Award and in 2016 he was awarded the European Data Innovator Award. Since May 2017, Ralf Klinkenberg is member of the steering committee of the platform for Learning Systems of the national German department for research and education (Bundes- ministerium für Bildung und Forschung (BMBF)), an innovation initiative of the Ger- man government via which the German government intents to promote the use of Machine Learning in industry and society. Ralf Klinkenberg is passionate about learn- ing in humans and machines as well as about how to leverage data with machine learning and predictive analytics to make organizations more data-driven, more agile, more efficient and effective, both from a business and a technical perspective.