基于数据仓库的教学管理系统应用研究
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摘要
近年来，我国高等院校招生规模不断扩大，但同时也出现了如生源质量下降，办学经费紧张，师资力量不足等新问题。如何提高管理水平和办学质量，是很多高校亟待解决的问题。目前多数高校中一些部门一般都建立了信息管理系统，如学生管理系统、教务管理系统、教师信息系统等。但分散在各个部门的信息资源缺乏统一的管理和组织，堆积了大量的历史数据。而学校管理决策人员很难从这些系统中综合出决策所需要的相关信息。因此，建立学校的数据仓库，将已有的管理数据进行综合管理、分析并挖掘出有用的信息，是提高学校竞争力，帮助管理者进行决策的一种方法。
本文分析了数据仓库技术及其应用，联机分析处理等相关技术，针对已有的管理系统，提出了一种基于数据仓库及OLAP技术的高校教学管理系统应用方案。论文详细介绍了系统的总体设计，包括概念模型、逻辑模型及物理模型的设计、系统的开发过程及结果的显示和分析。
系统运行结果表明，系统的设计达到了预期的目标。
In recent years, with the increasing enrollment scales in universities, some new problems arise such as fall of students' quality, lack of funds, and shortage of teachers. We find it urgent to improve management standard and quality of operation. At present, information management system, such as the student management system, teaching management system and teacher information system, has been established in some departments of a majority of universities. However, various resources of information is scattered in different departments without centralized management and organization, accumulating a large amount of historical data. It is hard for the management of the university to extract useful information for policy decisions from them. Therefore, it is a suitable way to build the data warehouse to comprehensively manage and analyze the existing data and extract the useful information, so as to help the management to make decisions and make the university more competitive.
This thesis analyzes the data warehouse technology and its application, as well as the relevant technology such as Online Analytical Processing (OLAP). On the basis of existing management system a program based on data warehouse and OLAP is put forward, which is applied in university teaching management system. The thesis introduces in detail the general design of the system, including the design of conception model, logic model and physics model, the development and implement process of the system, as well as the display and analysis of results.
It was indicated that the design of the system has reached the anticipated goal from the systematic operation result.
本文分析了数据仓库技术及其应用，联机分析处理等相关技术，针对已有的管理系统，提出了一种基于数据仓库及OLAP技术的高校教学管理系统应用方案。论文详细介绍了系统的总体设计，包括概念模型、逻辑模型及物理模型的设计、系统的开发过程及结果的显示和分析。
系统运行结果表明，系统的设计达到了预期的目标。
In recent years, with the increasing enrollment scales in universities, some new problems arise such as fall of students' quality, lack of funds, and shortage of teachers. We find it urgent to improve management standard and quality of operation. At present, information management system, such as the student management system, teaching management system and teacher information system, has been established in some departments of a majority of universities. However, various resources of information is scattered in different departments without centralized management and organization, accumulating a large amount of historical data. It is hard for the management of the university to extract useful information for policy decisions from them. Therefore, it is a suitable way to build the data warehouse to comprehensively manage and analyze the existing data and extract the useful information, so as to help the management to make decisions and make the university more competitive.
This thesis analyzes the data warehouse technology and its application, as well as the relevant technology such as Online Analytical Processing (OLAP). On the basis of existing management system a program based on data warehouse and OLAP is put forward, which is applied in university teaching management system. The thesis introduces in detail the general design of the system, including the design of conception model, logic model and physics model, the development and implement process of the system, as well as the display and analysis of results.
It was indicated that the design of the system has reached the anticipated goal from the systematic operation result.
引文
[1]陈京民．数据仓库原理设计与应用．中国水利水电出版社．2004．
[2]W．H．Inmon．Building the Date Warehouse(Third Edition)．机械工业出版社．2003．
[3]李爱凤，陈启买．基于数据仓库技术的教务管理系统(EAS)．现代计算机(总第253期)2007．2．
[4]黄羿等．基于数据仓库的学生成绩分析模型设计．信息技术．2007年第2期．
[5]丁知斌，袁方．基于数据仓库的数据挖掘技术在高校学生成绩分析中的应用．河北大学成人教育学院学报．2004，6(4)．
[6]雷松泽，李文轩．基于数据仓库的高校OLAP系统设计．现代电子技术．2005，20(总211期)．
[7]Moriarty T．What Is Metadata?．Database Programming and Design，1997，10(7)：57-59．
[8]Nigel Pendse．The OLAP Report-OLAP Architectures．OLAP concil，1999．
[9]陈涛，邓斌．数据仓库技术在高等学校的应用研究．山东农业大学学报(自然科学版)．2005，36(4)：591-594．
[10]孟跃红，黄智．数据仓库技术在高校教育管理中的应用．徐州师范大学学报(自然科学版)．2003，21(2)：69-71．
[11]周学君，杨敏．面向高校就业的数据仓库中数据析取技术及实现．三峡大学学报(自然科学版)．2005，27(3)．
[12]左楠等．高校数据仓库的构建技术研究．企业技术开发．2006，25(4)．
[13]Meredith M E．Designing Large Warehouses．Database Programming and Design，1996，9(6)：25-30．
[14]Inmon W H．The Data Warehouse and Data Mining．Communication of The ACM，1996，49(11)：49-50．
[15]Adlen S．Exploring the Data Warehouse Organizational and Cultural Issues．Database Programming and Design，1995，8(6)：25-27．
[16]Ken Orr．Data Warehouse Technology．http：／／www．dwinfocenter．org．2005．
[17]Erik Thorsen．OLAP and Data Mining：Creat a Total DSS Solution．Database Submit，1998．
[18]邓斌，李明东．数据集市技术在高校信息管理中的应用．山东农业大学学报(自然科学版)2004年，35(4)：611-614．
[19]Usama M Fayyad，Gregory Piatetsky-Shapiro et al．Advances in knowledge discovery and data mining．California：AAAUMIT Press，1996．
[20]Jay-Louise Weldon．Data mining and visualization．Database Programming and Design，May 1996，9(5)：21-24．
[21]李彩霞．基于Web的数据仓库技术及其在高校综合管理中的应用．河南农业大学学报，2006，40(3)：333-335．
[22]魏金强．多维分析技术在教务管理系统中的应用．北方工业大学硕士学位论文，2006．
[23]Anindya Datta，Helen Thomas．The cube data model：a conceptual model and algebra for on-line analytical processing in data warehouse[J]．Decision Support Systems，1999(27)，289-301．
[24]EDWARD HUNG,DAVID W．CHEUNG，BEN KAO．Optimization in Data Cube System Design[J]．Journal of Intelligent Information Systems．2004．23．1，17-45．
[25]于莉．基于高校学生信息库的数据挖掘．内蒙古大学硕士学位论文，2004．
[26]陈元丁．基于数据仓库的教务管理数据分析系统的设计．云南大学硕士学位论文，2005．
[27]Dimitri Theodoratos，Timos Sellis．Designing data warehouses[J]．DATA&KNOWLEDGE ENGINEERING．1999(31)，279-301．
[28]Arun Sen．Metadata management：past，present and future[J]．Decision Support Systems，2004(37)．151-173．
[29]朱继业．基于OLAP技术的教务综合管理系统的设计与实现．华东理工大学硕士学位论文，2004．
[30]葛福江．数据仓库技术在高校生源分析中的应用研究．河海大学硕士学位论，2006．
[31]郑赞红．维度建模技术研究及在高校中的应用．重庆大学硕士学位论文，2006．
[32]丁智斌．基于数据仓库和数据挖掘的高校学生成绩分析．河北大学，2005．
[33]Pat Minton．The Conformed ETL Architecture．DM Review．Sep2004，Vol．14：8-12．
[34]Tony Bain，Mike Benkovich，Robin Dewson etc．Professional SQL Server 2000 Data Warehousing with Analysis Services[M]，Wrox Press Ltd，414-422．
[35]Madsen M．Warehouse Design in The Aggregate．Database Programming and Design，1996，9(7)：45-51．
[36]Sheikboleslami G Cbatterjee S，Zhang A．Wave-Cluster：A multi-resolution clustering approach for very large spatiall databases．In：Proceedings of the 24th International Conference on Very Large Databases．New York，1998．428-439．
[37]Data mining：extending the information warehouse framework．White Paper， IBM Corporation, 1996.
[38] Laguna, Miguel A.; Marquis, Josh M.; Garcia, Francisco J. DocFlow: workflow based requirements elicitation, Infomuttion and Software Technology Volume: 45, Issue:6,April 15, 2003, pp.357-369.
[39] Jose Samos, Felix Saltor, Jaume Sistac and Agusti Bardes. Database architecture for data warehousing: an evolutionary approach. In DEXA 1998: 746-756.
[40] R. Rojas. Neural Networks: a systematic introduction. Springer-Verlag. 1996.
[41] Sridhar Ramaswamy, Rajeev Rastogi, Kyuseok Shim. Efficient Algorithms for Mining Outliers from Large Data Sets. SIGMOD Conference 2000: 427-438.
[42] Shao Fengjing, An Outlier-analysis Algorithm Based on the Reduction of Boundary Cells Influence, Proc. Of the 8a' Joint International Computer Conference, 2002.
[43] Stone. Classification and Regression Trees. Wadsworth International Group, 1984.
[44] Kaufman L, Rousseeuw PJ. Finding Groups in Data: an Introduction to Cluster Analysis, John Wiley & Sons, 1990.
[45] I.-J. Chiang, J. Y-Hsu. Fuzzy Classification Trees for Data Mining. working paper, 1999.2.
[46] WestphaIC, BlaxtonT. 1998. Data Mining Solutions, JohnWiley.
[47] Quinlan J R. Induction of decision tree. Machine Learning, 1986,81-106.
[48] Hughj,Watson. Recent Developments in Data Warehousing . Communications of the Association for Information Systems,2002.
[2]W．H．Inmon．Building the Date Warehouse(Third Edition)．机械工业出版社．2003．
[3]李爱凤，陈启买．基于数据仓库技术的教务管理系统(EAS)．现代计算机(总第253期)2007．2．
[4]黄羿等．基于数据仓库的学生成绩分析模型设计．信息技术．2007年第2期．
[5]丁知斌，袁方．基于数据仓库的数据挖掘技术在高校学生成绩分析中的应用．河北大学成人教育学院学报．2004，6(4)．
[6]雷松泽，李文轩．基于数据仓库的高校OLAP系统设计．现代电子技术．2005，20(总211期)．
[7]Moriarty T．What Is Metadata?．Database Programming and Design，1997，10(7)：57-59．
[8]Nigel Pendse．The OLAP Report-OLAP Architectures．OLAP concil，1999．
[9]陈涛，邓斌．数据仓库技术在高等学校的应用研究．山东农业大学学报(自然科学版)．2005，36(4)：591-594．
[10]孟跃红，黄智．数据仓库技术在高校教育管理中的应用．徐州师范大学学报(自然科学版)．2003，21(2)：69-71．
[11]周学君，杨敏．面向高校就业的数据仓库中数据析取技术及实现．三峡大学学报(自然科学版)．2005，27(3)．
[12]左楠等．高校数据仓库的构建技术研究．企业技术开发．2006，25(4)．
[13]Meredith M E．Designing Large Warehouses．Database Programming and Design，1996，9(6)：25-30．
[14]Inmon W H．The Data Warehouse and Data Mining．Communication of The ACM，1996，49(11)：49-50．
[15]Adlen S．Exploring the Data Warehouse Organizational and Cultural Issues．Database Programming and Design，1995，8(6)：25-27．
[16]Ken Orr．Data Warehouse Technology．http：／／www．dwinfocenter．org．2005．
[17]Erik Thorsen．OLAP and Data Mining：Creat a Total DSS Solution．Database Submit，1998．
[18]邓斌，李明东．数据集市技术在高校信息管理中的应用．山东农业大学学报(自然科学版)2004年，35(4)：611-614．
[19]Usama M Fayyad，Gregory Piatetsky-Shapiro et al．Advances in knowledge discovery and data mining．California：AAAUMIT Press，1996．
[20]Jay-Louise Weldon．Data mining and visualization．Database Programming and Design，May 1996，9(5)：21-24．
[21]李彩霞．基于Web的数据仓库技术及其在高校综合管理中的应用．河南农业大学学报，2006，40(3)：333-335．
[22]魏金强．多维分析技术在教务管理系统中的应用．北方工业大学硕士学位论文，2006．
[23]Anindya Datta，Helen Thomas．The cube data model：a conceptual model and algebra for on-line analytical processing in data warehouse[J]．Decision Support Systems，1999(27)，289-301．
[24]EDWARD HUNG,DAVID W．CHEUNG，BEN KAO．Optimization in Data Cube System Design[J]．Journal of Intelligent Information Systems．2004．23．1，17-45．
[25]于莉．基于高校学生信息库的数据挖掘．内蒙古大学硕士学位论文，2004．
[26]陈元丁．基于数据仓库的教务管理数据分析系统的设计．云南大学硕士学位论文，2005．
[27]Dimitri Theodoratos，Timos Sellis．Designing data warehouses[J]．DATA&KNOWLEDGE ENGINEERING．1999(31)，279-301．
[28]Arun Sen．Metadata management：past，present and future[J]．Decision Support Systems，2004(37)．151-173．
[29]朱继业．基于OLAP技术的教务综合管理系统的设计与实现．华东理工大学硕士学位论文，2004．
[30]葛福江．数据仓库技术在高校生源分析中的应用研究．河海大学硕士学位论，2006．
[31]郑赞红．维度建模技术研究及在高校中的应用．重庆大学硕士学位论文，2006．
[32]丁智斌．基于数据仓库和数据挖掘的高校学生成绩分析．河北大学，2005．
[33]Pat Minton．The Conformed ETL Architecture．DM Review．Sep2004，Vol．14：8-12．
[34]Tony Bain，Mike Benkovich，Robin Dewson etc．Professional SQL Server 2000 Data Warehousing with Analysis Services[M]，Wrox Press Ltd，414-422．
[35]Madsen M．Warehouse Design in The Aggregate．Database Programming and Design，1996，9(7)：45-51．
[36]Sheikboleslami G Cbatterjee S，Zhang A．Wave-Cluster：A multi-resolution clustering approach for very large spatiall databases．In：Proceedings of the 24th International Conference on Very Large Databases．New York，1998．428-439．
[37]Data mining：extending the information warehouse framework．White Paper， IBM Corporation, 1996.
[38] Laguna, Miguel A.; Marquis, Josh M.; Garcia, Francisco J. DocFlow: workflow based requirements elicitation, Infomuttion and Software Technology Volume: 45, Issue:6,April 15, 2003, pp.357-369.
[39] Jose Samos, Felix Saltor, Jaume Sistac and Agusti Bardes. Database architecture for data warehousing: an evolutionary approach. In DEXA 1998: 746-756.
[40] R. Rojas. Neural Networks: a systematic introduction. Springer-Verlag. 1996.
[41] Sridhar Ramaswamy, Rajeev Rastogi, Kyuseok Shim. Efficient Algorithms for Mining Outliers from Large Data Sets. SIGMOD Conference 2000: 427-438.
[42] Shao Fengjing, An Outlier-analysis Algorithm Based on the Reduction of Boundary Cells Influence, Proc. Of the 8a' Joint International Computer Conference, 2002.
[43] Stone. Classification and Regression Trees. Wadsworth International Group, 1984.
[44] Kaufman L, Rousseeuw PJ. Finding Groups in Data: an Introduction to Cluster Analysis, John Wiley & Sons, 1990.
[45] I.-J. Chiang, J. Y-Hsu. Fuzzy Classification Trees for Data Mining. working paper, 1999.2.
[46] WestphaIC, BlaxtonT. 1998. Data Mining Solutions, JohnWiley.
[47] Quinlan J R. Induction of decision tree. Machine Learning, 1986,81-106.
[48] Hughj,Watson. Recent Developments in Data Warehousing . Communications of the Association for Information Systems,2002.