The GOBIA method: Towards goal-oriented business intelligence architectures
Fekete D., Vossen G.
Forschungsartikel in Sammelband (Konferenz) | Peer reviewedZusammenfassung
Traditional Data Warehouse (DWH) architectures are challenged by numerous novel Big Data products. These tools are typically presented as alternatives or extensions for one or more of the layers of a typical DWH reference architecture. Still, there is no established joint reference architecture for both DWH and Big Data that is inherently aligned with business goals as implied by Business Intelligence (BI) projects. In this paper, a work-in-progress approach towards such custom BI architectures, the GOBIA method, is presented to address this gap, combining a BI reference architecture and a development process.
Details zur Publikation
Herausgeber*innen: Bergmann R., Görg S., Müller G.
Buchtitel: Proceedings of the LWA 2015 Workshops: KDML, FGWM, IR, and FGDB
Seitenbereich: 409-418
Verlag: CEUR-WS
Erscheinungsort: Trier, Germany
Titel der Reihe: Learning, Knowledge, Adaptation (ISSN: 1613-0073)
Nr. in Reihe: 1458
Status: Veröffentlicht
Veröffentlichungsjahr: 2015
Sprache, in der die Publikation verfasst ist: Englisch
Konferenz: Learning, Knowledge, Adaptation Workshops, LWA 2015: Knowledge Discovery, Data Mining and Machine Learning, KDML 2015, Knowledge Management, FGWM 2015, Information Retrieval, IR 2015 and Database Systems, FGDB 2015, Trier, Deutschland, undefined
Link zum Volltext: http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=84944342704&origin=inward
Stichwörter: Business Intelligence Architectures; Data Warehousing; Big Data; GOBIA
Autor*innen der Universität Münster
| Fekete, David | Lehrstuhl für Wirtschaftsinformatik (Prof. Vossen) (DBIS) |
| Vossen, Gottfried | Lehrstuhl für Wirtschaftsinformatik (Prof. Vossen) (DBIS) |