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Dorota Jelonek



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Dorota Jelonek


WSEAS Transactions on Computers


Print ISSN: 1109-2750
E-ISSN: 2224-2872

Volume 16, 2017

Notice: As of 2014 and for the forthcoming years, the publication frequency/periodicity of WSEAS Journals is adapted to the 'continuously updated' model. What this means is that instead of being separated into issues, new papers will be added on a continuous basis, allowing a more regular flow and shorter publication times. The papers will appear in reverse order, therefore the most recent one will be on top.



Leveraging Big Data for Competitive Advantage

AUTHORS: Dorota Jelonek

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ABSTRACT: Big data means data sets which are too large, too unstructured and too fast changing, to use traditional data management methods. Enterprises that want to collect and process this data need new solutions for data processing and analysis. The aim of this paper is to identify the potential of big data analytics (BDA) as a source of competitive advantage of manufacturing companies in the market. The aim was achieved using the desk research methodology and interviews with managers of large manufacturing enterprises. The article is divided into several sections, which cover the essence of big data, the competitive advantage of an enterprise from the Resource-based approach as well as big data analytics methods and analytic capabilities. The following parts discuss the architecture for big data analytics and provide some examples of big data analytics for business. The results of the study on the possibilities of using big data analytics as a source of competitive advantage in the market are also presented. The findings showed that big data can be a strategic resource and combined with analytics capabilities can create competitive factors both in cost strategy and in differentiation strategy.

KEYWORDS: big data, big data analytics, analytics capabilities, competitive advantage

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WSEAS Transactions on Computers, ISSN / E-ISSN: 1109-2750 / 2224-2872, Volume 16, 2017, Art. #16, pp. 146-154


Copyright © 2017 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution License 4.0

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