Humboldt-Universität zu Berlin - High Dimensional Nonstationary Time Series

IRTG1792DP2020 002

Service Data Analytics and Business Intelligence

Desheng Dang Wu
Wolfgang Karl Härdle

Abstract:
With growing economic globalization, the modern service sector is in great need
of business intelligence for data analytics and computational statistics. The
joint application of big data analytics, computational statistics and business
intelligence has great potential to make the engineering of advanced service
systems more efficient. The purpose of this COST issue is to publish high-
quality research papers (including reviews) that address the challenges of
service data analytics with business intelligence in the face of uncertainty and
risk. High quality contributions that are not yet published or that are not
under review by other journals or peer-reviewed conferences have been collected.
The resulting topic oriented special issue includes research on business
intelligence and computational statistics, data-driven financial engineering,
service data analytics and algorithms for optimizing the business engineering.
It also covers implementation issues of managing the service process,
computational statistics for risk analysis and novel theoretical and
computational models, data mining algorithms for risk management related
business applications.

Keywords:
Data Analytics, Business Intelligence Systems

JEL Classification:
C00