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An Integrated Multidimensional Modeling Approach to Access Big Data in Business Intelligence Platforms

机译:在业务智能平台中访问大数据的集成多维建模方法

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摘要

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.
机译:可用的大量信息及其异构性已经超过了当前数据管理技术的能力。处理大量结构化和非结构化数据(通常称为大数据)是一个热门的研究主题,也是一项技术挑战。在本文中,我们提出了一种旨在允许对不同的异构数据源进行OLAP查询的方法。提出的建模方法基于MapReduce范例,该范例将不同的格式集成到最新的RDF Data Cube格式中。我们的方法的优势在于,它允许用户进行查询以获取来自不同来源的数据,同时保持对可用数据的集成,全面视图。本文讨论了这种方法的优点和缺点以及实现方面的挑战。此外,在一个应用示例中说明了该方法。

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