Service Data Analytics and Business Intelligence

Desheng Dang Wu and Wolfgang Härdle

No 2020-002, IRTG 1792 Discussion Papers from Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series"

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 (search for similar items in EconPapers)
JEL-codes: C00 (search for similar items in EconPapers)
Date: 2020
New Economics Papers: this item is included in nep-big, nep-cmp and nep-rmg
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Persistent link: https://EconPapers.repec.org/RePEc:zbw:irtgdp:2020002

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