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

Abstract

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.

A Business Intelligence & Analytics Framework for Clean and Affordable Energy Data Analysis

“…Our first contribution is to bring the DSR process together with the BI&A value chain (see Figure 6). Only a few references have been identified treating the contribution of DSR to Business Intelligence &Analytics approaches [38,46]. The process of developing the final information artifact starts with problem identification and motivation, and setting the objectives of the solution.…”

“…Design Science Research (DSR) builds and evaluates artifacts, such as constructs, models, methods, or instantiations [37]. According to Mwilu et al [38], new artifacts can significantly boost the field of Business Intelligence &Analytics.…”

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“…Even so, a strong argument can be made to suggest that the field is indeed researchmore specifically, an implementation of design science research (also referred to as design research or constructive research; Vaishnavi and Kuechler 2004). Although it is a multidisciplinary field with broad applications, design science research is frequently applied to the development of information systems, including analytics-related products such as business intelligence tools (Mwilu et al 2016). Manson (2006) proposes that field of operational research fits in well with the design science research paradigm, and we suggest that this is true more generally for MWFA.…”

A conceptual framework for business intelligence critical success factors

“…Therefore, BI systems can be viewed as the next generation of DSSs (Arnott and Pervan, 2008). Through dashboards that display key performance indicators, and display current or historical data relative to organisational or individual targets on scorecards, BI systems are able to provide real-time information, create rich and precisely targeted analytics, and manage business processes (Mwilu et al, 2015). BI integrates data, which is stored and aggregated by the organisation.…”