论文河北网通基于数据仓库的帐务决策分析系统的设.doc

数据仓库论文：河北网通基于数据仓库的帐务决策分析系统的设计与实现【中文摘要】数据仓库技术是基于数学及统计学严谨逻辑思维的并达成“科学的判断、有效的行为”的一个工具。数据仓库技术也是一种达成“数据整合、知识管理”的有效手段。它从不同视角对企业经营各方面的信息进行精确分析,准确判断,为企业的决策者做出正确的决策提供了重要的支撑。典型的数据仓库系统,比如:经营分析系统,决策支持系统等等。也随着数据仓库系统带来的良好效果,各行各业的单位,已经能很好的接受“整合数据,从数据中找知识,运用数据知识、用数据说话”等新的关系到改良生产活动各环节、提高生产效率、发展生产力的理念。本文结合已有的数据仓库技术理论,对河北网通的基于数据仓库的账务决策分析系统项目进行了设计与实施。提出了面向数据仓库的账务决策分析的体系结构及相关主题域,并根据“从一个简明主题开始实施”的原则,采用自底向上的方法进行构建,首先建立部门数据集市,实现区域自治,对相关部门的应用进行分类复制,对每个数据集市进行数据重构,逐步扩展到企业数据仓库(EDW)。重点工作是在账务主题域的数据集市构建过程中实现了客户、账户、用户实体,帐单、欠费、存款、清单、产品、优惠实体等主题域信息,根据不同分析需求实现不同汇总粒度的划分和数据的分割,实现了不同数据源数据的集成等,并针对收益分析构造了多维模型,基于此模型利用固定(预定义)报表、图表、即席查询(Ad-Hoc)、EIS(Executive Information System)、多维动态分析、数据挖掘等展现方式,从不同维度、不同粒度、多种视角形象直观地显示分析数据。重点对计费系统账单数据进行OLAP分析,建立了面向计费系统的财务决策的数据集市。通过该项设计与实施,探索出了一种将数据仓库技术与具体应用相结合的有效的方法,以业务支撑系统的数据以及其他相关数据作为基础数据源,采用科学的数据抽取、整理、存储等方法,挖掘数据内部蕴藏的大量有用信息,通过科学的分析,做出可信的预测,从而为市场决策管理者和市场经营工作提供及时、准确、科学的辅助决策依据。本项应用为提高公司整体管理效率,确定决策分析方向提供了数据依据。本文的经验可供其它数据仓库项实施借鉴,研究成果经进一步完善和扩充可推广到与通信行业相关的各企业应用。【英文摘要】Data warehouse technology is a tool based on rigorous mathematical and statistical logical thinking to reach“scientific judgment and effective behavior,”but also some efficient approach to“data integration and knowledge management.”The technology conducts accurate analysis and judgment from different perspectives so as to provide key support for decision-making. Typical data warehouse system includes business analysis system, decision support system, etc. With the good results displayed from data warehouse systems, the concept has been well-accepted among organizations in various walks of life that“data integration, data application and data speak”do matter in the process of production improvement, and help develop production efficiency.Combining the existing data warehouse theory, the paper designs and operates the data warehouse-based Hebei Netcom accounting decision-analysis project, and further proposes the data warehouse-oriented accounting decision-analysis system structure and related domain fields. The system is started“from a simple domain”and set up according to bottom-up approach. The department data mart is first established to achieve regional autonomy and classified copying of department applications, followed by data restructure of data marts and further expansion into Enterprise Data Warehouse (EDW).During the data mart building, the key task lies in the realization of domain information, including client, account, entity, bill, arrear, deposit, inventory, product and offered target. Analysis of various demand leads to different aggregate granule partition lattice and data categorization, achieving the data integration from various sources. Moreover, multi-dimension model is constructed for benefit analysis. By using fixed (predefined) reports, charts, ad hoc query (Ad-Hoc), EIS (Executive Information System), multi-dimensional dynamic analysis, data mining and other displaying methods, the model achieves the visual data demonstration and analysis from different dimensions, granule sizes and perspectives. The billing data is especially focused on for OLAP analysis so as to establish a data mart for financial decision-making in billing system.By designing and implementing the project, an effective approach has been explored to combine data warehouse technology and specific applications. Taking data from operation-supportive system and other relevant systems as the underlying data source, the approach employs scientific data extraction, collation and storage methods to dig out a lot of useful information, and makes reliable predictions after scientific analysis, serving as timely, accurate and reasonable support for decision-making and market operation.The application of the project provides data support for companies to improve overall management efficiency and determine direction of decisions. The experience of the paper could serve as experiment for other data warehouse projects and be applied to telecommunication-related enterprises after further perfection and expansion.【关键词】数据仓库 数据集市 OLAP 粒度划分 EDW【英文关键词】Data warehouse data mart OLAP Granule Partition Lattice EDW【目录】河北网通基于数据仓库的帐务决策分析系统的设计与实现摘要4-5ABSTRACT5-6第一章 引言10-141.1 研究背景和意义10-111.2 河北网通数据管理的现状11-121.3 本文主要研究内容12-131.4 论文组织结构13-14第二章 相关理论知识与技术14-202.1 什么是数据仓库142.2 操作型数据库与数据仓库的区别14-152.3 创建数据仓库的意义152.4 建立数据仓库的基本步骤15-162.5 数据集市、OLAP 与数据挖掘16-192.5.1 数据集市的概念16-172.5.2 数据集市的模型172.5.3 元数据管理17-182.5.4 OLAP（联机分析处理）18-192.5.5 数据挖掘192.6 本章小结19-20第三章 需求分析与总体设计20-303.1 数据仓库的体系结构20-213.2 数据仓库的总体设计21-223.3 数据仓库的具体设计过程22-263.3.1 主题域的确定22-233.3.2 粒度的划分23-243.3.3 数据分割243.3.4 数据仓库模式设计243.3.5 创建数据仓库表和数据准备区24-253.3.6 析取、清理和转换数据253.3.7 数据装入数据仓库253.3.8 建立分析应用25-263.4 数据仓库的开发过程26-293.4.1 任务和环境的评估263.4.2 需求的收集和分析26-273.4.3 构造数据仓库273.4.4 创建多维数据集27-283.4.5 建立分析应用283.4.6 数据仓库技术的培训283.4.7 回顾、总结及再发展28-293.5 本章小结29-30第四章 详细设计与实现30-464.1 基于数据仓库的账务决策分析系统的设计30-354.1.1 体系结构与设计流程30-314.1.2 确定系统需求31-324.1.3 已有的工作基础324.1.4 确定数据库服务器和数据分析工具32-334.1.5 确定主要的主题域33-344.1.6 确定基于数据仓库的账务决策分析的数据组织方法344.1.7 确定基于数据仓库的账务决策分析的分析方法344.1.8 确定基于数据仓库的账务决策分析的数据展现方法34-354.2 面向计费系统账务决策的数据集市的设计及实施35-454.2.1 设计目标的确定35-374.2.2 确定粒度层次划分374.2.3