Service Analytics

Understanding complex and decentralized service systems would not be possible without the emergence of intelligent and semi-automatic tools and processes for data analytics. Just tapping streams, e.g., from social networks or electronic markets will most certainly overcharge leadership and may even lead to poor strategic decision making.

Addressing this availability-usability gap entails both the technical handling and analysis of large amounts of data as well as making sense out of high-dimensional data. Techniques required herein include machine learning, prediction, classification, and dimension reduction.