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Graph BI : Analytics: Current State and Future Challenges

机译:图BI&:分析:当前状态和未来挑战

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In an increasingly competitive market, making well-informed decisions requires the analysis of a wide range of heterogeneous, large and complex data. This paper focuses on the emerging field of graph warehousing. Graphs are widespread structures that yield a great expressive power. They are used for modeling highly complex and interconnected domains, and efficiently solving emerging big data application. This paper presents the current status and open challenges of graph BI and analytics, and motivates the need for new warehousing frameworks aware of the topological nature of graphs. We survey the topics of graph modeling, management, processing and analysis in graph warehouses. Then we conclude by discussing future research directions and positioning them within a unified architecture of a graph BI and analytics framework.
机译:在竞争日益激烈的市场中,做出明智的决策需要分析各种各样的异构,大型和复杂数据。本文主要关注图仓库的新兴领域。图是广泛的结构,可产生强大的表达能力。它们用于对高度复杂和相互关联的域进行建模,并有效地解决新兴的大数据应用程序。本文介绍了图BI和分析的当前状态和未解决的挑战,并激发了对了解图的拓扑性质的新仓库框架的需求。我们调查图仓库中图建模,管理,处理和分析的主题。然后,我们通过讨论未来的研究方向并将其定位在图形BI和分析框架的统一体系结构中进行总结。

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