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A Data Modelling Method for Big Data Warehouses

机译:大数据仓库的数据建模方法

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摘要

Current increases on the data characteristics that define the advent of Big Data have led to a novel area of research, by updating (or even replacing) traditional Data Warehousing solutions into the age of large volumes of fast and diverse data. Although relevant, such endeavors have failed to provide complete and general design and implementations approaches. A recent work has however proposed a general-purpose, integrated, detailed and thoroughly evaluated approach for the design and implementation of Big Data Warehouses. From that, this work proposes, demonstrates and validates a method for modelling Big Data Warehouses, based on a set of sequential rules that aim to semi-automatically translate a traditional relational data model into the proposed Big Data Warehouse model. Positive results have shown how such method can empower the scientific and organizational domains in their efforts to more easily migrate from common traditional Data Warehouses into Big Data Warehousing solutions.
机译:定义大数据的到来的数据特性的最新增长通过将传统的数据仓库解决方案更新(甚至替代)到大量快速而多样化的数据时代,导致了一个新的研究领域。尽管相关,但是这些努力未能提供完整和通用的设计和实现方法。但是,最近的工作为大数据仓库的设计和实现提出了一种通用的,综合的,详细的和经过全面评估的方法。由此,这项工作提出,演示并验证了一种基于一组顺序规则的建模大数据仓库的方法,这些规则旨在将传统的关系数据模型半自动地转换为所提议的大数据仓库模型。积极的结果表明,这种方法如何能够使科学和组织领域更加努力地从普通的传统数据仓库迁移到大数据仓库解决方案。

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