Turning Multidimensional Big Data Analytics into Practice: Design and Implementation of ClustCube Big-Data Tools in Real-Life Scenarios

Alfredo Cuzzocrea, Abderraouf Hafsaoui, Ismail Benlaredj
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Abstract

Multidimensional Big Data Analytics is an emerging area that marries the capabilities of OLAP with modern Big Data Analytics. Essentially, the idea is engrafting multidimensional models into Big Data analytics processes to gain into expressive power of the overall discovery task. ClustCube is a state-of-the-art model that combines OLAP and Clustering, thus delving into practical and well-understood advantages in the context of real-life applications and systems. In this paper, we show how ClustCube can effectively and efficiently realizing nice tools for supporting Multidimensional Big Data Analytics, and assess these tools in the context of real-life research projects.
将多维大数据分析付诸实践:在实际生活场景中设计和实施 ClustCube 大数据工具
多维大数据分析是一个新兴领域,它将 OLAP 的能力与现代大数据分析相结合。从本质上讲,其理念是将多维模型嫁接到大数据分析流程中,以获得整体发现任务的表达能力。ClustCube 是将 OLAP 和聚类相结合的最新模型,因此在实际应用和系统中具有实用和广为人知的优势。在本文中,我们展示了 ClustCube 如何高效地实现支持多维大数据分析的好工具,并结合实际研究项目对这些工具进行了评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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