An integrated multidimensional modeling approach to access big data in business intelligence platforms

Authors:
Alejandro Maté;Hector Llorens;Elisa de Gregorio
Affiliations:
Lucentia Research Group, Department of Software and Computing Systems, University of Alicante, Spain;Lucentia Research Group, Department of Software and Computing Systems, University of Alicante, Spain;Lucentia Research Group, Department of Software and Computing Systems, University of Alicante, Spain
Venue:
ER'12 Proceedings of the 2012 international conference on Advances in Conceptual Modeling
Year:
2012

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Abstract

The huge amount of information available and its heterogeneity has surpassed the capacity of current data management technologies. Dealing with that huge amounts of structured and unstructured data, often referred as Big Data, is a hot research topic and a technological challenge. In this paper, we present an approach aimed to allow OLAP queries over different, heterogeneous, data sources. The modeling approach proposed is based on a MapReduce paradigm, which integrates different formats into the recent RDF Data Cube format. The benefits of our approach are that it allows a user to make queries that need data from different sources while maintaining, at the same time, an integrated, comprehensive view of the data available. The paper discusses the advantages and disadvantages, as well as the implementation challenges that such approach presents. Furthermore, the approach is illustrated in an example of application.