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Incorporating external data into a BI solution at a public waste management organization
University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. (Produktion och automatiseringsteknik, Production and Automation Engineering)ORCID iD: 0000-0002-8619-3776
University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. (Produktion och automatiseringsteknik, Production and Automation Engineering)ORCID iD: 0000-0003-3973-3394
2019 (English)In: International Journal of Business Intelligence Research, ISSN 1947-3591, E-ISSN 1947-3605, Vol. 10, no 2, p. 36-56Article in journal (Refereed) Published
Abstract [en]

Organizations are showing an increasing interest in incorporating external data into their business intelligence solutions. Such data allows for advanced analytics and enables more comprehensive and inclusive decision-making. However, external data incorporation is relatively unexplored in the literature, and scientifically published details on up-and-running BI solutions are very sparse. In addition, published literature concerning the incorporation of external data into BI solutions is often rather synoptic or rather old (originating from data warehouse related literature). Therefore, the authors present the results of an action case study at a public waste management organization, illustrating detailed aspects of external data incorporation related to the back-end of the solution such as data selection, source characteristics, acquisition technologies and frequencies, and integration approaches. Given that the external origin of the data poses specific problems that must be overcome in order to allow for successful incorporation initiatives, special attention was paid to such problems. Copyright © 2019, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

Place, publisher, year, edition, pages
IGI Global, 2019. Vol. 10, no 2, p. 36-56
Keywords [en]
Business Intelligence, Case Study, External Data, Waste Management
National Category
Other Computer and Information Science Media Engineering Information Systems
Research subject
Production and Automation Engineering
Identifiers
URN: urn:nbn:se:his:diva-17479DOI: 10.4018/IJBIR.2019070104Scopus ID: 2-s2.0-85068688761OAI: oai:DiVA.org:his-17479DiVA, id: diva2:1339125
Note

EISBN13: 9781522566939

Available from: 2019-07-25 Created: 2019-07-25 Last updated: 2023-06-20Bibliographically approved

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Strand, MattiasSyberfeldt, Anna

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