The GOBIA method: Towards goal-oriented business intelligence architectures
Abstract
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.
Keywords
Business Intelligence Architectures; Data Warehousing; Big Data; GOBIA
Cite as
Fekete, D., & Vossen, G. (2015). The GOBIA method: Towards goal-oriented business intelligence architectures. In Bergmann, R., Görg, S., & Müller, G. (Eds.), Proceedings of the LWA 2015 Workshops: KDML, FGWM, IR, and FGDB (pp. 409–418). Learning, Knowledge, Adaptation: Vol. 1458. Trier, Germany: CEUR-WS.Details
Publication type
Research article in proceedings (conference)
Peer reviewed
Yes
Publication status
Published
Year
2015
Conference
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
Venue
Trier, Deutschland
Book title
Proceedings of the LWA 2015 Workshops: KDML, FGWM, IR, and FGDB
Editor
Bergmann R., Görg S., Müller G.
Start page
409
End page
418
Volume
1458
Title of series
Learning, Knowledge, Adaptation
Publisher
CEUR-WS
Place
Trier, Germany
Language
English
ISSN
1613-0073
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