Soars比较购物分析数据仓库的设计
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摘要
比较购物是随着电子商务发展而出现的一种新型电子购物模式。随着企业业务的发展,购物网站中积累的历史数据越来越多。同时,与同行企业之间业务竞争也越来越激烈。企业决策部门需要从这些海量数据中,有效地抽取有价值的信息,对用户的行为进行分析,以找出更好的销售模式,发现引导用户购买习惯的销售策略,从而促进企业的业务发展。另外每个网站都有一套独立的报表系统,也使得数据分散,信息孤立,资源冗余。因此构建一个集成的,数据一致性的数据源,整合所有数据资源,为有效地分析提供一个企业级数据平台。
首先分析了比较购物当前分析系统的现状,然后针对数据仓库设计过程以及其中的关键技术问题进行了详细地探讨。在此基础上,讨论了针对Web应用系统的ETL系统设计,分析数据抽取、转换、装载,形成数据结构化的过程;然后讨论了数据仓库模型设计,主题域的确定,粒度层次划分,性能优化处理,以及数据仓库平台的构建过程;最后展望数据仓库在比较购物分析中的应用前景。
Comparison shopping is a new kind of electronic shopping patterns as the development of the e-commerce. With the development of businesses, more and more historical data in shopping website has been accumulated. At the same time the business competition between the same industry enterprises becomes more and more fierce. The decision-making department has to collect valuable information from the massive data to analysis the user behavior so as to find better sales model and to propose a sales plan which can guide the users' buying habits, and then promote the business development of enterprises. In addition each website has a set of separate report system, which makes data scattered, information isolated, and resources redundant. Therefore an integrated, consistent data sources is established to integrate all data sources and to supply an enterprise data platform for effective analysis.
Firstly, the current analytics situation for comparison shopping is introduced and then the processing procedure of creating data warehouse and some main issues are discussed. ETL system design for web application system is discussed including the issues of how to extract and translate and load from the unstructured or semi-structured data to structured data. Then the model design of data warehouse is discussed, the theme domain is confirmed, the discussion of dimension's granularity and performance optimization is made, as well as the process of establishing the data warehouse platform is discussed. Finally, it's necessary to prospect the outlook for applications of data warehouse on analyzing the user's behavior in comparison shopping.
首先分析了比较购物当前分析系统的现状,然后针对数据仓库设计过程以及其中的关键技术问题进行了详细地探讨。在此基础上,讨论了针对Web应用系统的ETL系统设计,分析数据抽取、转换、装载,形成数据结构化的过程;然后讨论了数据仓库模型设计,主题域的确定,粒度层次划分,性能优化处理,以及数据仓库平台的构建过程;最后展望数据仓库在比较购物分析中的应用前景。
Comparison shopping is a new kind of electronic shopping patterns as the development of the e-commerce. With the development of businesses, more and more historical data in shopping website has been accumulated. At the same time the business competition between the same industry enterprises becomes more and more fierce. The decision-making department has to collect valuable information from the massive data to analysis the user behavior so as to find better sales model and to propose a sales plan which can guide the users' buying habits, and then promote the business development of enterprises. In addition each website has a set of separate report system, which makes data scattered, information isolated, and resources redundant. Therefore an integrated, consistent data sources is established to integrate all data sources and to supply an enterprise data platform for effective analysis.
Firstly, the current analytics situation for comparison shopping is introduced and then the processing procedure of creating data warehouse and some main issues are discussed. ETL system design for web application system is discussed including the issues of how to extract and translate and load from the unstructured or semi-structured data to structured data. Then the model design of data warehouse is discussed, the theme domain is confirmed, the discussion of dimension's granularity and performance optimization is made, as well as the process of establishing the data warehouse platform is discussed. Finally, it's necessary to prospect the outlook for applications of data warehouse on analyzing the user's behavior in comparison shopping.
引文
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[2]Michael Block.Online holiday shopping survey[R].Taming The Beast.2007.http://www.tamingthebeast.net/blog/ecommerce/online-shopp-ing-survey-1107.html
[3]Catherine Seda 著.谢婷,周至等译.搜索引擎广告:网络营销的成功之路[M].电子工业出版社.2005,4:11-13
[4]中文全文检索网.如何做好一个垂直搜索引擎[EB/OU].中文全文检索网站,2006,http://www.fullsearcher.com
[5]W.H.Inmon.Building the Data Warehouse[M].New York:John Wiley & Sons,1996
[6]Michel Schneider.Well-formed Data Warehouse Structures[C].Blaise Pascal University.2005
[7]张云涛,龚玲编著.商业智能设计、部署与实现[M].电子工业出版社,2004,3:24
[8]Jiawei Han,Micheline Kamber著.范明,孟晓峰译.数据挖掘概念与技术[M].机械工业出版社,2004,2:55-56
[9]Otis Gospodnetic,Erik Hatcher著.Lucene In Action[M].电子工业出版社.2006,1:9
[10]冯英健著.网络营销基础及实践[M].清华大学出版社.2007,4:158
[11]杨怡玲著.Web日志挖掘中的数据准备与用户浏览模式识别[D].西安交通大学,1999
[12]Apache.org.Apache HTTP Server Document EB/OL/.Http://www.apache.org.http://httpd.apache.org/docs/2.2/logs.html
[13]戴子良著.数据仓库建模与ETL实践技巧[DB/CD].世纪乐知网站.http://blo-g.csdn.net/DaiZiLiang/archive/2006/11/27/1417391.aspx
[14]Lilian Hobbs,Susan Hillson,Shilpa Lawande,Pete Smith.Oracle Database 10G Data Warehousing[M].Elsevier,2005,2:66-67
[15]C.J.Date 著.孟小峰,王珊等译.数据库系统导论[M].机械工业出版社,2000,2:20-39
[16]滕永昌 编著.Oracle 9i数据库管理员使用大全[M].清华大学出版社,2004,21:767-771
[17]Abraham Silberschatz,Henry F.Korth 著.Database System Concepts [M].机械工业出版社.1999,11:346-356