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PublicationData Ecosystems: A New Dimension of Value Creation Using AI and Machine LearningMachine learning and artificial intelligence have become crucial factors for the competitiveness of individual companies and entire economies. Yet their successful deployment requires access to a large volume of training data often not even available to the largest corporations. The rise of trustworthy federated digital ecosystems will significantly improve data availability for all participants and thus will allow a quantum leap for the widespread adoption of artificial intelligence at all scales of companies and in all sectors of the economy. In this chapter, we will explain how AI systems are built with data science and machine learning principles and describe how this leads to AI platforms. We will detail the principles of distributed learning which represents a perfect match with the principles of distributed data ecosystems and discuss how trust, as a central value proposition of modern ecosystems, carries over to creating trustworthy AI systems.
PublicationFraunhofer Big Data and Artificial Intelligence AllianceBig data is a management issue across sectors and promises to deliver a competitive advantage via structured knowledge, increased efficiency and value creation. Within companies, there is significant demand for big data skills, individual business models, and technological solutions. Fraunhofer assists companies to identify and mine their valuable data. Experts from Fraunhofers Big Data and Artificial Intelligence Alliance demonstrate how companies can benefit from an intelligent enrichment and analysis of their data.
PublicationFraunhofer-Allianz Big DataBig Data ist branchenübergreifend ein Management-Thema und verspricht der Wirtschaft Vorsprung durch strukturiertes Wissen, mehr Effizienz und Wertschöpfung. In den Unternehmen gibt es einen hohen Bedarf an Big-Data- Kompetenzen, individuellen Geschäftsmodellen und technischen Lösungen. Fraunhofer unterstützt Unternehmen dabei, ihre Datenschätze zu identifizieren und zu heben. Experten der Fraunhofer-Allianz Big Data zeigen auf, wie Unternehmen von der intelligenten Anreicherung und Analyse ihrer Daten profitieren können.
PublicationSpatial data mining in practiceAlmost any data can be referenced in geographic space. Such data permit advanced analyses that utilize the position and relationships of objects in space as well as geographic background information. Even though spatial data mining is still a young research discipline, in the past years research advances have shown that the particular challenges of spatial data can be mastered and that the technology is ready for practical application when spatial aspects are treated as an integrated part of data mining and model building. In this chapter in particular, we give a detailed description of several customer projects that we have carried out and which all involve customized data mining solutions for business relevant tasks. The applications range from customer segmentation to the prediction of traffic frequencies and the analysis of GPS trajectories. They have been selected to demonstrate key challenges, to provide advanced solutions and to arouse further research questions.