SOA enabled ELTA: approach in designing business intelligence solutions in Era of Big Data

V. Dmitriyev, T. Mahmoud, Pablo Michel Marín-Ortega
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引用次数: 5

Abstract

The current work presents a new approach for designing business intelligence solutions. In the Era of Big Data, former and robust analytical concepts and utilities need to adapt themselves to the changed market circumstances. The main focus of this work is to address the acceleration of building process of a “data-centric” Business Intelligence (BI) solution besides preparing BI solutions for Big Data utilization. This research addresses the following goals: reducing the time spent during business intelligence solution’s design phase; achieving flexibility of BI solution by adding new data sources; and preparing BI solution for utilizing Big Data concepts. This research proposes an extension of the existing Extract, Load and Transform (ELT) approach to the new one Extract, Load, Transform and Analyze (ELTA) supported by service-orientation concept. Additionally, the proposed model incorporates Service-Oriented Architecture concept as a mediator for the transformation phase. On one side, such incorporation brings flexibility to the BI solution and on the other side; it reduces the complexity of the whole system by moving some responsibilities to external authorities.
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SOA支持的ELTA:大数据时代商业智能解决方案的设计方法
目前的工作提供了一种设计商业智能解决方案的新方法。在大数据时代,以前稳健的分析概念和实用程序需要适应不断变化的市场环境。除了为大数据利用率准备BI解决方案外,这项工作的主要重点是加快“以数据为中心”的商业智能(BI)解决方案的构建过程。本研究旨在实现以下目标:减少商业智能解决方案设计阶段所花费的时间;通过添加新的数据源实现BI解决方案的灵活性;以及为利用大数据概念准备BI解决方案。本研究提出将现有的提取、加载和转换(ELT)方法扩展到以服务为导向的新方法提取、加载、转换和分析(ELTA)。此外,所提出的模型结合了面向服务的体系结构概念,作为转换阶段的中介。一方面,这样的结合为BI解决方案带来了灵活性,另一方面,它也为BI带来了灵活性;它通过将一些责任转移到外部机构来降低整个系统的复杂性。
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来源期刊
CiteScore
6.30
自引率
18.20%
发文量
99
审稿时长
12 weeks
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