數(shù)據(jù)倉庫論文：河北網(wǎng)通基于數(shù)據(jù)倉庫的帳務(wù)決策分析系統(tǒng)的設(shè)計與實現(xiàn)

1、數(shù)據(jù)倉庫論文：河北網(wǎng)通基于數(shù)據(jù)倉庫的帳務(wù)決策分析系統(tǒng)的設(shè)計與實現(xiàn)【中文摘要】數(shù)據(jù)倉庫技術(shù)是基于數(shù)學(xué)及統(tǒng)計學(xué)嚴謹邏輯思維的并達成“科學(xué)的判斷、有效的行為”的一個工具。數(shù)據(jù)倉庫技術(shù)也是一種達成“數(shù)據(jù)整合、知識管理”的有效手段。它從不同視角對企業(yè)經(jīng)營各方面的信息進行精確分析,準確判斷,為企業(yè)的決策者做出正確的決策提供了重要的支撐。典型的數(shù)據(jù)倉庫系統(tǒng),比如:經(jīng)營分析系統(tǒng),決策支持系統(tǒng)等等。也隨著數(shù)據(jù)倉庫系統(tǒng)帶來的良好效果,各行各業(yè)的單位,已經(jīng)能很好的接受“整合數(shù)據(jù),從數(shù)據(jù)中找知識,運用數(shù)據(jù)知識、用數(shù)據(jù)說話”等新的關(guān)系到改良生產(chǎn)活動各環(huán)節(jié)、提高生產(chǎn)效率、發(fā)展生產(chǎn)力的理念。本文結(jié)合已有的數(shù)據(jù)倉庫技術(shù)理論,

2、對河北網(wǎng)通的基于數(shù)據(jù)倉庫的賬務(wù)決策分析系統(tǒng)項目進行了設(shè)計與實施。提出了面向數(shù)據(jù)倉庫的賬務(wù)決策分析的體系結(jié)構(gòu)及相關(guān)主題域,并根據(jù)“從一個簡明主題開始實施”的原則,采用自底向上的方法進行構(gòu)建,首先建立部門數(shù)據(jù)集市,實現(xiàn)區(qū)域自治,對相關(guān)部門的應(yīng)用進行分類復(fù)制,對每個數(shù)據(jù)集市進行數(shù)據(jù)重構(gòu),逐步擴展到企業(yè)數(shù)據(jù)倉庫(EDW)。重點工作是在賬務(wù)主題域的數(shù)據(jù)集市構(gòu)建過程中實現(xiàn)了客戶、賬戶、用戶實體,帳單、欠費、存款、清單、產(chǎn)品、優(yōu)惠實體等主題域信息,根據(jù)不同分析需求實現(xiàn)不同匯總粒度的劃分和數(shù)據(jù)的分割,實現(xiàn)了不同數(shù)據(jù)源數(shù)據(jù)的集成等,并針對收益分析構(gòu)造了多維模型,基于此模型利用固定(預(yù)定義)報表、圖表、即席查詢(

3、Ad-Hoc)、EIS(Executive Information System)、多維動態(tài)分析、數(shù)據(jù)挖掘等展現(xiàn)方式,從不同維度、不同粒度、多種視角形象直觀地顯示分析數(shù)據(jù)。重點對計費系統(tǒng)賬單數(shù)據(jù)進行OLAP分析,建立了面向計費系統(tǒng)的財務(wù)決策的數(shù)據(jù)集市。通過該項設(shè)計與實施,探索出了一種將數(shù)據(jù)倉庫技術(shù)與具體應(yīng)用相結(jié)合的有效的方法,以業(yè)務(wù)支撐系統(tǒng)的數(shù)據(jù)以及其他相關(guān)數(shù)據(jù)作為基礎(chǔ)數(shù)據(jù)源,采用科學(xué)的數(shù)據(jù)抽取、整理、存儲等方法,挖掘數(shù)據(jù)內(nèi)部蘊藏的大量有用信息,通過科學(xué)的分析,做出可信的預(yù)測,從而為市場決策管理者和市場經(jīng)營工作提供及時、準確、科學(xué)的輔助決策依據(jù)。本項應(yīng)用為提高公司整體管理效率,確定決策分析方向

4、提供了數(shù)據(jù)依據(jù)。本文的經(jīng)驗可供其它數(shù)據(jù)倉庫項實施借鑒,研究成果經(jīng)進一步完善和擴充可推廣到與通信行業(yè)相關(guān)的各企業(yè)應(yīng)用?！居⑽恼緿ata 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

5、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

6、 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 war

7、ehouse-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

8、 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, includin

9、g 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

10、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 siz

11、es 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 applica

12、tions. 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 ti

13、mely, 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 wareho

14、use projects and be applied to telecommunication-related enterprises after further perfection and expansion.【關(guān)鍵詞】數(shù)據(jù)倉庫 數(shù)據(jù)集市 OLAP 粒度劃分 EDW【英文關(guān)鍵詞】Data warehouse data mart OLAP Granule Partition Lattice EDW【目錄】河北網(wǎng)通基于數(shù)據(jù)倉庫的帳務(wù)決策分析系統(tǒng)的設(shè)計與實現(xiàn)摘要4-5ABSTRACT5-6第一章 引言10-141.1 研究背景和意義10-111.2 河北網(wǎng)通數(shù)據(jù)管理的現(xiàn)狀11-121.3 本文

15、主要研究內(nèi)容12-131.4 論文組織結(jié)構(gòu)13-14第二章 相關(guān)理論知識與技術(shù)14-202.1 什么是數(shù)據(jù)倉庫142.2 操作型數(shù)據(jù)庫與數(shù)據(jù)倉庫的區(qū)別14-152.3 創(chuàng)建數(shù)據(jù)倉庫的意義152.4 建立數(shù)據(jù)倉庫的基本步驟15-162.5 數(shù)據(jù)集市、OLAP 與數(shù)據(jù)挖掘16-192.5.1 數(shù)據(jù)集市的概念16-172.5.2 數(shù)據(jù)集市的模型172.5.3 元數(shù)據(jù)管理17-182.5.4 OLAP（聯(lián)機分析處理）18-192.5.5 數(shù)據(jù)挖掘192.6 本章小結(jié)19-20第三章 需求分析與總體設(shè)計20-303.1 數(shù)據(jù)倉庫的體系結(jié)構(gòu)20-213.2 數(shù)據(jù)倉庫的總體設(shè)計21-223.3 數(shù)據(jù)倉庫的具

16、體設(shè)計過程22-263.3.1 主題域的確定22-233.3.2 粒度的劃分23-243.3.3 數(shù)據(jù)分割243.3.4 數(shù)據(jù)倉庫模式設(shè)計243.3.5 創(chuàng)建數(shù)據(jù)倉庫表和數(shù)據(jù)準備區(qū)24-253.3.6 析取、清理和轉(zhuǎn)換數(shù)據(jù)253.3.7 數(shù)據(jù)裝入數(shù)據(jù)倉庫253.3.8 建立分析應(yīng)用25-263.4 數(shù)據(jù)倉庫的開發(fā)過程26-293.4.1 任務(wù)和環(huán)境的評估263.4.2 需求的收集和分析26-273.4.3 構(gòu)造數(shù)據(jù)倉庫273.4.4 創(chuàng)建多維數(shù)據(jù)集27-283.4.5 建立分析應(yīng)用283.4.6 數(shù)據(jù)倉庫技術(shù)的培訓(xùn)283.4.7 回顧、總結(jié)及再發(fā)展28-293.5 本章小結(jié)29-30第四章 詳細設(shè)計與實現(xiàn)30-464.1 基于數(shù)據(jù)倉庫的賬務(wù)決策分析系統(tǒng)的設(shè)計30-354.1.1 體系結(jié)構(gòu)與設(shè)計流程30-314.1.2 確定系統(tǒng)需求31-324.1.3 已有的工作基礎(chǔ)324.1.4 確定數(shù)據(jù)庫服務(wù)器和數(shù)據(jù)分析工具32-334.1.5 確定主要的主題域33-344.1.6 確定基于數(shù)據(jù)倉庫的賬務(wù)決策分析的數(shù)據(jù)組織方法344.1.7 確定基于數(shù)據(jù)倉庫的賬務(wù)決策分析的分析方法344.1.8 確定基于數(shù)據(jù)倉庫的賬務(wù)決策分析的數(shù)據(jù)展現(xiàn)方法34-354.2 面向計費系統(tǒng)賬務(wù)決策的數(shù)據(jù)集市的設(shè)計及實施35-454.2.1 設(shè)計目標(biāo)的確定35-374.2.2 確定粒度層次劃分374.2.3