A conceptual framework for delivering cost effective business intelligence solutions as a service

Muriithi, Gerald Maina; Kotzé, Eduan

doi:10.1145/2513456.2513502

Cited by 15 publications

(13 citation statements)

References 9 publications

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“…Proponen Cloud BI y realizan una prueba de concepto con el uso de un framework sobre un consorcio de PYMES obteniendo como resultado un RSI mayor al 100% gracias al uso de herramientas de BI sobre Cloud [18]. Muriithi (2013) encuentra como problema que la crisis ha obligado a las empresas a buscar soluciones que ayuden a optimizar sus recursos, por lo cual usa un framework de Cloud BI y simula la implementación en universidades sudafricanas para validarlo [10]. Agostino y Solberg (2013), observan la falta de adopción de Cloud BI por las PYMES respondiendo la pregunta: ¿Cuáles son los factores clave de éxito para la adopción de una solución de Cloud BI en las PYMES?…”

Section: Cloud Computing Y Bianda Aplicación En Pymesunclassified

Modelo de inteligencia de negocios y analítica en la nube para pymes del sector retail en Perú

Inga

Huaranga

2018

ing. Solidar

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Introducción: este artículo es producto de la investigación “Modelo de inteligencia de negocios y analítica en la nube para pymes del sector retail en Perú”, realizada durante el 2016 en la Facultad de Ingeniería de la Universidad Peruana de Ciencias Aplicadas (UPC) en Lima, Perú.Problema: las investigaciones revisadas determinan que las pymes retail peruanas tienen un índice alto de necesidad de información para la toma de decisiones en materia de planificación y gestión de inventarios.Objetivo: diseñar un modelo tecnológico que permita la implementación de una solución de business intelligence y analytics mediante el uso de servicios de cloud computing.Metodología: se partió de una revisión de la literatura sobre los beneficios de migración e implementación de business intelligence y analytics sobre cloud en pymes norteamericanas, europeas y asiáticas. A partir de esto se propone un modelo tecnológico orientado a las pymes retail peruanas y se describe cada uno de sus componentes.Resultados: se valida el modelo mediante su implementación en una pyme retail peruana en la que se realiza una evaluación de indicadores financieros, así como por medio de encuestas a expertos en las tecnologías.Conclusión: el modelo permite a las pymes integrar y procesar sus datos con el fin de obtener información relevante y oportuna para la optimización de inventario.Originalidad: la literatura sobre este tipo de implementaciones en pymes retail peruanas orientadas a la mejora de toma de decisiones es escaza.Limitaciones: el modelo propuesto solo es aplicable a pymes retail que hagan uso de sistemas transaccionales en el registro de sus operaciones.

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Section: Cloud Computing Y Bianda Aplicación En Pymesunclassified

Modelo de inteligencia de negocios y analítica en la nube para pymes del sector retail en Perú

Inga

Huaranga

2018

ing. Solidar

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“…Muriithi and Kotzé introduced another procedure (methodology) for BI migration [38]. This procedure includes three following steps: i) Situational analysis: this step consists of the current evaluation of an organization to identify potential opportunities for cloud BI.…”

Section: Bi As a Wholementioning

confidence: 99%

Design science research contribution to business intelligence in the cloud — A systematic literature review

Mwilu

Comyn-Wattiau

Prat

2016

Future Generation Computer Systems

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Business intelligence (BI) helps managers make informed decisions. In the age of big data, BI technology provides essential support for decision making. Cloud computing also attracts many organizations because of its potential: ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources (e.g. networks, servers, storage, applications, and services). This paper focuses on the deployment of BI in the cloud, from the vantage point of design science research (DSR). We produce a state of the art of research pertaining to BI in the cloud, following the methodology of systematic literature review. This literature review especially exhibits the different artifacts proposed by design science researchers regarding BI in the cloud. To structure the literature review, we propose a framework composed of two dimensions: artifact type and BI step. In particular, we propose a typology of artifact types, refining the coarse-grained typology commonly used in DSR. We use the two-dimensional framework both to map the current state of DSR regarding BI in the cloud, and to elicit future research avenues in terms of design science artifacts for BI in the cloud. The contribution is threefold: the literature review may help DSR researchers get an overview of this active research domain; the two-dimensional framework facilitates the understanding of different research streams; finally, the proposed future topics may guide researchers in identifying promising research avenues.

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“…In an organizational context the BI application supports the analysis and application of captured information in order to make strategic, tactical and operational decisions. Muriithi and Kotzé [42] state that the adoption and use of BI systems within the enterprise remains low despite the potential benefits of an effective BI system. For optimal adoption, the user needs to be able to interact with the application in such a way that the business decision is not inhibited by an overly complex user interface.…”

Section: Usability In Business Intelligencementioning

confidence: 99%

Usability Evaluation for Business Intelligence Applications: A User Support Perspective

Jooste¹,

Biljon²,

Mentz³

2014

SACJ

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Business Intelligence (BI) applications provide business information to drive decision support. Usability is one of the factors determining the optimal use and eventual benefit derived from BI applications. The documented need for more BI usability research together with the practical necessity for BI evaluation guidelines in the mining industry provides the rationale for this study. The purpose of the study was to investigate the usability evaluation of BI applications in the context of a coal mining organization. The research is guided by the question: How can existing usability criteria be customized to evaluate the usability of BI applications. The research design included user observation, heuristic evaluation and a survey. Based on observations made during user support on a BI application used at a coal mining organization a log of usability issues was compiled. The usability issues extracted from this log was compared and contrasted with general usability criteria from literature to synthesize an initial set of BI usability evaluation criteria. These criteria were used as the basis for a heuristic evaluation of the BI application used at the coal mining organization. The same BI application was also evaluated using the Software Usability Measurement Inventory (SUMI) standardized questionnaire. The results from the two evaluations were triangulated and then compared with the BI user issues again to contextualize the findings and synthesize a validated and refined set of criteria. The main contribution of the study is the usability evaluation criteria for BI applications presented as guidelines. These guidelines deviate from existing evaluation guidelines in the emphasis on information architecture, learnability and operability.

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A conceptual framework for delivering cost effective business intelligence solutions as a service

Cited by 15 publications

References 9 publications

Modelo de inteligencia de negocios y analítica en la nube para pymes del sector retail en Perú

Modelo de inteligencia de negocios y analítica en la nube para pymes del sector retail en Perú

Design science research contribution to business intelligence in the cloud — A systematic literature review

Usability Evaluation for Business Intelligence Applications: A User Support Perspective

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