数据仓库技术及在电信系统应用的研究
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摘要
数据仓库技术起源于对大量数据进行处理的需要，是随着业务应用的需要而产生的。与传统的数据库技术相比，数据仓库为决策分析提供了更好的支持，跳出了传统的联机处理的范畴。因此近几年来，数据仓库技术发展很快，并在各个行业都得到了应用。
随着垄断格局的打破，国内电信运营商间的竞争也越来越激烈，而网络服务质量等方面的差别也在逐渐减少，单纯的价格战将对竞争的双方造成损失。因此，电信企业都在寻求改善服务质量、提高市场竞争力的方法。面对这种越来越激烈的市场竞争，电信企业迫切地需要提高企业内部的科学决策能力，增强在市场经营等方面的正确判断能力，因此，电信运营商需要数据仓库技术。
另一方面，电信运营商积累了大量的业务运营数据，这些数据都是已经电子化的数据，通过数据仓库技术，可以从这些用户数据中发现很多有价值的信息，例如用户的消费行为分析特征等。根据这些消费行为特征，市场部门就可以提供针对性更强的市场服务策略，并且节约了市场营销的成本。因此，电信企业的大量的电子化数据为其建设数据仓库奠定了技术基础。
本文首先阐述了数据仓库的基本原理，数据挖掘的基本概念，数据挖掘常用的方法。然后就其在电信领域中的应用进行了分析，提出了电信领域常见的分析主题，并且对典型的主题提出了OLAP分析的多维数据结构的建立，具体的分析方法。提出了具体的电信领域的决策分析主题，选择适当的数据挖掘算法及其相应的数据挖掘的实施过程，并对挖掘结果进行了分析。
Data warehouse technology originated from and go on need that dispose of a large number of data, emerge in pace with need that the business uses. Compared with traditional data base technology, data warehouse offer a kind support for making decision and analysis, Jump out category that deal with traditional OLTP. So in recent years, data warehouse technology develop very quickly, and has got application in varios trade.
Along with the breaking of the monopolize pattern the competition among the domestic telecommunication operators is fiercer and fiercer, and difference of network service quality, etc. reduce gradually too. Simple Warrior of price cause demage to both sides in competition. So telecommunication enterprise are seeking method of improving service quality and raising market competitiveness, faced with the fiercer and fiecer market competition , telecommunication enterprise need improving science decision ability urgently, Strengthen correct judgement in such aspects as market management, so telecommunication operator need warehouse technology.
On the other hand, telecommunication enterprise has accumulated a large amount of business running data, these are all electronic data , a lot of valuable information can be found from these user data, for example, consumer behavior of user analyse feature . According to these consumer behavior feature, market department can offer stronger pertinence tactics for market service, And has economized the cost of the marketing. So a large number of electron data of telecommunication enterprise build data warehouse establishing the technological foundation.
At first , this text has explained the basic principle of the data warehouse, how to set up the model of OLAP, Analytical method of OLAP. The basic conception that the data mining , the commonly used method of the data mining. Second , application in elecommunication field was analyzied, the writer put forward common analysis theme in telecommunication field, Propose multidimensional structure that OLAP analyse to typical theme, Concrete analytical method. Put forward concrete telecommunication decision of field analyse theme ,
choose proper data mining algorithm and corresponding implementation data mining process , And analyze the result of data mininging .
随着垄断格局的打破，国内电信运营商间的竞争也越来越激烈，而网络服务质量等方面的差别也在逐渐减少，单纯的价格战将对竞争的双方造成损失。因此，电信企业都在寻求改善服务质量、提高市场竞争力的方法。面对这种越来越激烈的市场竞争，电信企业迫切地需要提高企业内部的科学决策能力，增强在市场经营等方面的正确判断能力，因此，电信运营商需要数据仓库技术。
另一方面，电信运营商积累了大量的业务运营数据，这些数据都是已经电子化的数据，通过数据仓库技术，可以从这些用户数据中发现很多有价值的信息，例如用户的消费行为分析特征等。根据这些消费行为特征，市场部门就可以提供针对性更强的市场服务策略，并且节约了市场营销的成本。因此，电信企业的大量的电子化数据为其建设数据仓库奠定了技术基础。
本文首先阐述了数据仓库的基本原理，数据挖掘的基本概念，数据挖掘常用的方法。然后就其在电信领域中的应用进行了分析，提出了电信领域常见的分析主题，并且对典型的主题提出了OLAP分析的多维数据结构的建立，具体的分析方法。提出了具体的电信领域的决策分析主题，选择适当的数据挖掘算法及其相应的数据挖掘的实施过程，并对挖掘结果进行了分析。
Data warehouse technology originated from and go on need that dispose of a large number of data, emerge in pace with need that the business uses. Compared with traditional data base technology, data warehouse offer a kind support for making decision and analysis, Jump out category that deal with traditional OLTP. So in recent years, data warehouse technology develop very quickly, and has got application in varios trade.
Along with the breaking of the monopolize pattern the competition among the domestic telecommunication operators is fiercer and fiercer, and difference of network service quality, etc. reduce gradually too. Simple Warrior of price cause demage to both sides in competition. So telecommunication enterprise are seeking method of improving service quality and raising market competitiveness, faced with the fiercer and fiecer market competition , telecommunication enterprise need improving science decision ability urgently, Strengthen correct judgement in such aspects as market management, so telecommunication operator need warehouse technology.
On the other hand, telecommunication enterprise has accumulated a large amount of business running data, these are all electronic data , a lot of valuable information can be found from these user data, for example, consumer behavior of user analyse feature . According to these consumer behavior feature, market department can offer stronger pertinence tactics for market service, And has economized the cost of the marketing. So a large number of electron data of telecommunication enterprise build data warehouse establishing the technological foundation.
At first , this text has explained the basic principle of the data warehouse, how to set up the model of OLAP, Analytical method of OLAP. The basic conception that the data mining , the commonly used method of the data mining. Second , application in elecommunication field was analyzied, the writer put forward common analysis theme in telecommunication field, Propose multidimensional structure that OLAP analyse to typical theme, Concrete analytical method. Put forward concrete telecommunication decision of field analyse theme ,
choose proper data mining algorithm and corresponding implementation data mining process , And analyze the result of data mininging .
引文
1 Inmon WH..Building Data Warehouse. Second Edition. John Wiley. 1996.
2 R. Groth. Data Mining:Building Competitive Advantage. Prentice-Hall, 1997
3 Ric Sperley. The Enterprise Data Warehouse. Volume Ⅰ: Planning Building And mplement-ation. Prentice Hall PTR, 1999.
4 Morgan Kaufmann, 2001 Alex Berson, Stephen Smith, Kurt Thearling. Building Data Mining Applications for CRM. McGraw-Hill Companies. 2000
5 Lou Agosta. Tth Essential Guide to Data Warehousing. Prentice-Hall, 2000.
6 Willianrm A Giovinazzo. Object-Oriented Data Warehouse Design. 2000.
7 Ronald Swift. Accelerating Customer Relationshipe: Using CRM and Relationship Technologies. Prentice- Hall. 2001.
8 Jiawei Han, Micheline Kamber. Data Mining: Concepts and Techniques.
9 R. Kimball, The Data Warehouse Toolkit. John Wiley &Sons, 1996.
10 E. Thomsen. OLAP Solutions: Building Multidimensional Information Systems. John Wiley &Sons. 1997.
11 王珊等，数据仓库技术与联机分析处理。北京：科学出版社，1998
12 罗纳德．S．史威福特，客户关系管理——加速利润和优势提升，杨东龙等译。北京：中国经济出版社，2001
13 黄梯云，管理信息系统，北京：高等教育出版社，1999
14 罗运模等，SOL Server 2000数据仓库应用与开发。北京：人民邮电出版社，2001
15 陈国良等。遗传算法及其应用。北京：人民邮电出版社，1996
16 朱爱群。客户关系管理与数据挖掘，北京：中国财政经济出版社，2001
17 李纪华，王珊，OLAP两种支持技术，计算机世界，1996-7-15
18 陈京民。数据析取技术在市场营销中的作用。商业研究。2000(3)
19 陈京民。IT／IS战略管理若干问题探索。电子与信息化。2000(9)
20 陈京民。数据仓库开发的规划研究，计算机与网络，2000(5)
21 陈京民等，企业的客户关系管理(CRM)实施过程，企业经济，2000(5)
22 邹雯，陈文伟，数据开采中的遗传算法，计算机世界，1997-6-30
23 马建军，陈文伟，数据开采中的集合论方法，计算机世界。1997-6-30
24 王珊，罗力，从数据库到数据仓库，中国人民在学数据与知识工程研究所，1997
25 胡侃，夏绍伟。基于大型数据仓库的数据采掘，软件学报，1998
26 林宇等，数据仓库原理与实践，人民邮电出版社。2003
2 R. Groth. Data Mining:Building Competitive Advantage. Prentice-Hall, 1997
3 Ric Sperley. The Enterprise Data Warehouse. Volume Ⅰ: Planning Building And mplement-ation. Prentice Hall PTR, 1999.
4 Morgan Kaufmann, 2001 Alex Berson, Stephen Smith, Kurt Thearling. Building Data Mining Applications for CRM. McGraw-Hill Companies. 2000
5 Lou Agosta. Tth Essential Guide to Data Warehousing. Prentice-Hall, 2000.
6 Willianrm A Giovinazzo. Object-Oriented Data Warehouse Design. 2000.
7 Ronald Swift. Accelerating Customer Relationshipe: Using CRM and Relationship Technologies. Prentice- Hall. 2001.
8 Jiawei Han, Micheline Kamber. Data Mining: Concepts and Techniques.
9 R. Kimball, The Data Warehouse Toolkit. John Wiley &Sons, 1996.
10 E. Thomsen. OLAP Solutions: Building Multidimensional Information Systems. John Wiley &Sons. 1997.
11 王珊等，数据仓库技术与联机分析处理。北京：科学出版社，1998
12 罗纳德．S．史威福特，客户关系管理——加速利润和优势提升，杨东龙等译。北京：中国经济出版社，2001
13 黄梯云，管理信息系统，北京：高等教育出版社，1999
14 罗运模等，SOL Server 2000数据仓库应用与开发。北京：人民邮电出版社，2001
15 陈国良等。遗传算法及其应用。北京：人民邮电出版社，1996
16 朱爱群。客户关系管理与数据挖掘，北京：中国财政经济出版社，2001
17 李纪华，王珊，OLAP两种支持技术，计算机世界，1996-7-15
18 陈京民。数据析取技术在市场营销中的作用。商业研究。2000(3)
19 陈京民。IT／IS战略管理若干问题探索。电子与信息化。2000(9)
20 陈京民。数据仓库开发的规划研究，计算机与网络，2000(5)
21 陈京民等，企业的客户关系管理(CRM)实施过程，企业经济，2000(5)
22 邹雯，陈文伟，数据开采中的遗传算法，计算机世界，1997-6-30
23 马建军，陈文伟，数据开采中的集合论方法，计算机世界。1997-6-30
24 王珊，罗力，从数据库到数据仓库，中国人民在学数据与知识工程研究所，1997
25 胡侃，夏绍伟。基于大型数据仓库的数据采掘，软件学报，1998
26 林宇等，数据仓库原理与实践，人民邮电出版社。2003