Big Data Analytics for developing countries – Using the Cloud for Operational BI in Health

dc.contributor.authorBraa, Jørn
dc.contributor.authorPurkayastha, Saptarshi
dc.date.accessioned2022-10-11T22:00:28Z
dc.date.available2022-10-11T22:00:28Z
dc.date.issued2013
dc.description.abstractThe multi-layered view of digital divide suggests there is inequality of access to ICT, inequality of capability to exploit ICT and inequality of outcomes after exploiting ICT. This is evidently clear in the health systems of developing countries. In this paper, we look at cloud computing being able to provide computing as a utility service that might bridge this digital divide for Health Information Systems in developing countries. We highlight the role of Operational Business Intelligence (BI) tools to be able to make better decisions in health service provisioning. Through the case of DHIS2 software and its Analytics-as-a-Service (AaaS) model, we look at how tools can exploit Cloud computing capabilities to perform analytics on Big Data that is resulting from integration of health data from multiple sources. Beyond looking at purely warehousing techniques, we suggest understanding Big Data from Organizational Capabilities and expanding organizational capabilities by offloading computing as a utility to vendors through cloud computing.en_US
dc.identifier.citationPurkayastha, S. and Braa, J. (2013), Big Data Analytics for developing countries – Using the Cloud for Operational BI in Health. The Electronic Journal of Information Systems in Developing Countries, 59: 1-17. https://doi.org/10.1002/j.1681-4835.2013.tb00420.xen_US
dc.identifier.urihttps://hdl.handle.net/1805/30328
dc.language.isoen_USen_US
dc.publisherWileyen_US
dc.relation.isversionof10.1002/j.1681-4835.2013.tb00420.xen_US
dc.subjectCloud computingen_US
dc.subjectAnalytics-as-a-Serviceen_US
dc.subjectBig dataen_US
dc.subjectDigital divideen_US
dc.subjectHealth Information Systemsen_US
dc.titleBig Data Analytics for developing countries – Using the Cloud for Operational BI in Healthen_US
dc.typePreprinten_US
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