A proposed model for data warehouse ETL processes

数据仓库 计算机科学 量纲建模 数据库 在线分析处理 星型模式 概念模型 概念图式 统一建模语言 个性化 过程(计算) 数据挖掘 软件 数据库设计 数据库架构 万维网 心理学 发展心理学 性别图式理论 程序设计语言 操作系统
作者
Shaker El–Sappagh,Abdeltawab Hendawi,Ali Hamed El Bastawissy
出处
期刊:Journal of King Saud University - Computer and Information Sciences [Elsevier BV]
卷期号:23 (2): 91-104 被引量:147
标识
DOI:10.1016/j.jksuci.2011.05.005
摘要

Extraction–transformation–loading (ETL) tools are pieces of software responsible for the extraction of data from several sources, its cleansing, customization, reformatting, integration, and insertion into a data warehouse. Building the ETL process is potentially one of the biggest tasks of building a warehouse; it is complex, time consuming, and consumes most of data warehouse project's implementation efforts, costs, and resources. Building a data warehouse requires focusing closely on understanding three main areas: the source area, the destination area, and the mapping area (ETL processes). The source area has standard models such as entity relationship diagram, and the destination area has standard models such as star schema, but the mapping area has not a standard model till now. In spite of the importance of ETL processes, little research has been done in this area due to its complexity. There is a clear lack of a standard model that can be used to represent the ETL scenarios. In this paper we will try to navigate through the efforts done to conceptualize the ETL processes. Research in the field of modeling ETL processes can be categorized into three main approaches: Modeling based on mapping expressions and guidelines, modeling based on conceptual constructs, and modeling based on UML environment. These projects try to represent the main mapping activities at the conceptual level. Due to the variation and differences between the proposed solutions for the conceptual design of ETL processes and due to their limitations, this paper also will propose a model for conceptual design of ETL processes. The proposed model is built upon the enhancement of the models in the previous models to support some missing mapping features.
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