Self-service Business Intelligence over On-Demand IoT Data: A New Design Methodology Based on Rapid Prototyping

Author(s):  
Julian Eduardo Plazas ◽  
Sandro Bimonte ◽  
Michel Schneider ◽  
Christophe de Vaulx ◽  
Juan Carlos Corrales
2013 ◽  
Vol 9 (2) ◽  
pp. 66-88 ◽  
Author(s):  
Alberto Abelló ◽  
Jérôme Darmont ◽  
Lorena Etcheverry ◽  
Matteo Golfarelli ◽  
Jose-Norberto Mazón ◽  
...  

Self-service business intelligence is about enabling non-expert users to make well-informed decisions by enriching the decision process with situational data, i.e., data that have a narrow focus on a specific business problem and, typically, a short lifespan for a small group of users. Often, these data are not owned and controlled by the decision maker; their search, extraction, integration, and storage for reuse or sharing should be accomplished by decision makers without any intervention by designers or programmers. The goal of this paper is to present the framework we envision to support self-service business intelligence and the related research challenges; the underlying core idea is the notion of fusion cubes, i.e., multidimensional cubes that can be dynamically extended both in their schema and their instances, and in which situational data and metadata are associated with quality and provenance annotations.


2017 ◽  
Vol 13 (3) ◽  
pp. 65-85 ◽  
Author(s):  
Mohammad Daradkeh ◽  
Radwan Moh'd Al-Dwairi

Despite the growing popularity of self-service business intelligence (SSBI) tools, empirical research that investigates their acceptance by business professionals is still scarce. This paper presents and tests an integrated model of the antecedents of users' acceptance of SSBI tools in business enterprises. The proposed model is developed based on the technology acceptance model (TAM) and incorporating information and system quality from DeLone and McLean IS success model. It also includes an important factor from the business intelligence literature called analysis quality. To test the model, data were collected through a questionnaire survey from 331 business users working in a variety of industries in Jordan. Data were analysed using structural equation modeling (SEM) techniques. The results demonstrated that the three quality factors– information quality, system quality and analysis quality – are key antecedents of perceived usefulness and ease of use, which in turn were found to be strong predictors of users' intention to use SSBI tools. The findings of this study provide several implications for research and practice, and thus should help in the design and deployment of more user-accepted SSBI tools.


Author(s):  
Christian Lennerholt ◽  
Joeri Van Laere ◽  
Eva Söderström

2020 ◽  
Vol 29 (1) ◽  
pp. 1-26
Author(s):  
Jens Passlick ◽  
Nadine Guhr ◽  
Benedikt Lebek ◽  
Michael H. Breitner

Controlling ◽  
2021 ◽  
Vol 33 (6) ◽  
pp. 50-56
Author(s):  
Marvin Jagals ◽  
Erik Karger ◽  
und Marco Boehle

Self-Service BI gestattet Fachbereichen innerhalb einer Organisation in Eigenverantwortung Analysen zu erstellen. In der Praxis existieren dazu jedoch besonders auf Managementebene diverse Herausforderungen. Im Rahmen dieses Beitrags werden Gestaltungsempfehlungen erörtert, die der Managementpraxis zu einer erfolgreichen Implementierung verhelfen.


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