Social BI (SBI) is the emerging discipline that aims at combining corporate data with textual user-generated content (UGC) to let decision-makers analyze their business based on the trends perceived from the environment. Despite the increasing diffusion of SBI applications, no specific and organic design methodology is available yet. In this paper we propose an iterative methodology for designing and maintaining SBI applications that reorganizes the activities and tasks normally carried out by practitioners. Effective support to quick maintenance iterations is a key feature in this context due to the huge dynamism of the UGC and to the pressing need of immediately perceiving and timely reacting to changes in the environment. The paper is completed by two case studies of real SBI projects, related to Italian politics and to the consumer goods area respectively, aimed at proving that the adoption of a structured methodology positively impacts on the project success.

Matteo Francia, Matteo Golfarelli, Stefano Rizzi (2014). A Methodology for Social BI. BytePress - ACM [10.1145/2628194.2628250].

A Methodology for Social BI

FRANCIA, MATTEO;GOLFARELLI, MATTEO;RIZZI, STEFANO
2014

Abstract

Social BI (SBI) is the emerging discipline that aims at combining corporate data with textual user-generated content (UGC) to let decision-makers analyze their business based on the trends perceived from the environment. Despite the increasing diffusion of SBI applications, no specific and organic design methodology is available yet. In this paper we propose an iterative methodology for designing and maintaining SBI applications that reorganizes the activities and tasks normally carried out by practitioners. Effective support to quick maintenance iterations is a key feature in this context due to the huge dynamism of the UGC and to the pressing need of immediately perceiving and timely reacting to changes in the environment. The paper is completed by two case studies of real SBI projects, related to Italian politics and to the consumer goods area respectively, aimed at proving that the adoption of a structured methodology positively impacts on the project success.
2014
Proceedings IDEAS 2014
207
216
Matteo Francia, Matteo Golfarelli, Stefano Rizzi (2014). A Methodology for Social BI. BytePress - ACM [10.1145/2628194.2628250].
Matteo Francia; Matteo Golfarelli; Stefano Rizzi
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/317318
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