基于数据仓库的邮政金融客户管理系统的设计与实现
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摘要
当今世界充满了剧烈竞争,正确及时的决策是企业生存和发展的最重要环节。现在,愈来愈多的企业认识到,要想在竞争中取胜,获得更大的收益,必须分析当前和历史的生产业务数据,以及相关环境的相关数据,自动快速获取其中有用的决策信息,为企业提供快速、准确和方便的决策支持。而基于数据仓库的商业智能的出现,成为解决这一问题的有效途径。商业智能也称作BI(BusinessIntelligence),通常被理解为将企业中现有的数据转化为知识,帮助企业做出明智的业务经营决策的工具,为了将数据转化为知识,需要利用数据仓库、联机分析处理(OLAP)工具和数据挖掘等技术。数据仓库的作用就在于“发现数据价值,从数据中获得回报”。通过数据仓库,收集、汇总和分析企业的各种数据,提高工作效率、提供更好的客户服务的方法。邮政金融客户管理系统就是以数据仓库(DW)和商业智能(BI)技术为核心,在后台采用高性能的数据仓库专用引擎来构建基础数据平台,前端应用则采用成熟的商业智能分析工具,通过集成的WEB门户为提供统一入口,完成对各功能子系统的访问需求。本文通过邮政金融客户管理系统的设计和实现进一步论证了数据仓库在提高企业决策支持水平、信息质量、应变能力的重要意义和作用。
Now the world has filled the fierce competition, the correct prompt decision-making is the enterprise survival and the development most important link. Now, the more and more enterprises realized, must want to win in the competition, obtains a greater income, must analyze current and the historical production service data, as well as the correlation environment correlation data, automatically fast gains useful decision information, provides fast, accurate and the convenient policy-making support for the enterprise. But based on the data warehouse business intelligence appearance, becomes solves this question effective way. The business intelligence also is called as BI (Business Intelligence), usually was understood for the existing data transforms the enterprise in as the knowledge, helps the enterprise to make the unwise account executive decision-making the tool, in order to transforms the data as the knowledge, needs to use the data warehouse, on-line analysis processing (OLAP) technology and so on tool and data mining. The data warehouse function lies in "the discovery data value, obtains the repayment from the data". Through the data warehouse, the collection, compiles with analysis enterprise's each kind of data, enhances the working efficiency, provide the better customer service the method. This article logarithm has carried on the discussion according to the warehouse technology in the commercial intelligence application, the main content includes: Elaborated the commercial intelligence concept, the use and the development, and introduced the commercial intelligence project implementation step, has analyzed the enterprise service logic model and the data quality constructs the data warehouse to the success the vital role, and further proved the data warehouse through the postal savings customer management system management system design and the application to raise the enterprise decision-making support level, the information quality, the strain capacity vital significance and the function. Elaborated with emphasis based on the data warehouse business intelligence system overall structural design, the data warehouse system structural design.
Now the world has filled the fierce competition, the correct prompt decision-making is the enterprise survival and the development most important link. Now, the more and more enterprises realized, must want to win in the competition, obtains a greater income, must analyze current and the historical production service data, as well as the correlation environment correlation data, automatically fast gains useful decision information, provides fast, accurate and the convenient policy-making support for the enterprise. But based on the data warehouse business intelligence appearance, becomes solves this question effective way. The business intelligence also is called as BI (Business Intelligence), usually was understood for the existing data transforms the enterprise in as the knowledge, helps the enterprise to make the unwise account executive decision-making the tool, in order to transforms the data as the knowledge, needs to use the data warehouse, on-line analysis processing (OLAP) technology and so on tool and data mining. The data warehouse function lies in "the discovery data value, obtains the repayment from the data". Through the data warehouse, the collection, compiles with analysis enterprise's each kind of data, enhances the working efficiency, provide the better customer service the method. This article logarithm has carried on the discussion according to the warehouse technology in the commercial intelligence application, the main content includes: Elaborated the commercial intelligence concept, the use and the development, and introduced the commercial intelligence project implementation step, has analyzed the enterprise service logic model and the data quality constructs the data warehouse to the success the vital role, and further proved the data warehouse through the postal savings customer management system management system design and the application to raise the enterprise decision-making support level, the information quality, the strain capacity vital significance and the function. Elaborated with emphasis based on the data warehouse business intelligence system overall structural design, the data warehouse system structural design.
引文
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[17]Sybase构建银行数据仓库--Sybase数据仓库解决方案在招商银行的应用软件世界 2000(12)
[2]Inmon W H.《Building the Data Warehouse》 John Wiley & Sons,Inc.Second Edition,1996.
[3](美)荫蒙(Inmon,W.H)著,王志海 等译《数据仓库》(原书第4版)机械工业出版社2004
[4]陈文伟《数据仓库与数据挖掘教程》清华大学出版社 2006
[5]池太崴编著《数据仓库结构设计与实施--建造信息系统的金字塔》电子工业出版社 2005
[6]S.Chauduri,U.Dayal.An Overview of Data Warehousing and OLAP Technology.ACM SIGMOD Record,vol 26,no.1:65-74,1997
[7]Kimball R,Reeves L,Roos M,Thornthwaite W.The Datawarehouse Lifecycle Toolkit:Expert Methods for Designing.Developing and Deploying Datawarehouses,John Wiley & Sons,Inc.1998.
[8]Harjinder S.GILL 等著,王仲谋 刘书舟 译,数据仓库-客户/服务器计算指南,清华大学出版社,西蒙舒.斯特国际出版公司,1997
[9]Tom Hammergren 著,曹增强 王备战 等译,数据仓库技术(Data Wharehousing:Building the Corporate Knowledge Base),中国水利水电出版社,1998
[10]周永銮 数据仓库技术简介 电子周刊 2001.07.21
[11]Oracle 中国有限公司.Oracle数据仓库解决方案.Oracle技术白皮书,2000.
[12]Oracle Corporation.Oracle9i for e-Business:Business Intelligence.Oracle Technical White Paper,2001.
[13]Oracle Corporation.Oraclegi for Data Warehousingand Business Intelligence.Oracle Business White Paper,2002.
[14]Venky Harinarayan,Anand Rajaraman and Jeffrey D.Ullman Implementing data cubes efficiently SIGMOD96
[15]Yihong Zhao,Prasad M.Deshpande,Jeffrey F.Naughton An array-based algorithm for simultaneous multidimensional aggregates.SIGMOD,1997
[16]S.Sarawagi,M.Stonebraker,"Efficient Organization of Large Multidimensional Arrays",In Proc.of ICDE,1994
[17]Sybase构建银行数据仓库--Sybase数据仓库解决方案在招商银行的应用软件世界 2000(12)