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Annals of Computer Science and Information Systems, Volume 13

Communication Papers of the 2017 Federated Conference on Computer Science and Information Systems

Business Intelligence Platform for Big Data based on Scalable Distributed Two-Layer Data Store


DOI: http://dx.doi.org/10.15439/2017F195

Citation: Communication Papers of the 2017 Federated Conference on Computer Science and Information Systems, M. Ganzha, L. Maciaszek, M. Paprzycki (eds). ACSIS, Vol. 13, pages 177182 ()

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Abstract. Data mining is one of the main business intelligence technique. The volume of Big Data expands in such a way that the classical Business Intelligence methods need to be redefined. First, the organization of large data sets requires new distributed database architectures. Second, it is necessary to develop distributed data processing models that provide a high degree of scalability.In this paper we introduce fully scalable BI platform that is suitable for the most common data processing issues. The platform is based on our scalable distributed two-layer data store, which is competitive to existing NoSQL distributed data base systems. We show examples and experimental results showing advantages of our approach.


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