Developing Strategic Reports for National Co-Operative of Malaysia (Angkasa) Using Data Warehouse and Decision Tree Model

Managing an organization requires access to information in order to monitor activities and assess performance. Business Intelligence (BI) solutions provide organizations with timley, itegrated information that is crucial to the understanding of their business. Data Warehouse (DW) technology is one o...

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Main Author: Al-Badri, Ayad H. Mousa
Format: Thesis
Language:eng
eng
Published: 2012
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Online Access:https://etd.uum.edu.my/2931/1/Ayad_H._Mousa_Al-Badri.pdf
https://etd.uum.edu.my/2931/2/Ayad_H._Mousa_Al-Badri-1.pdf
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id my-uum-etd.2931
record_format uketd_dc
institution Universiti Utara Malaysia
collection UUM ETD
language eng
eng
advisor Shiratuddin, Norshuhada
Abu Bakar, Muhamad Shahbani
topic QA76 Computer software
spellingShingle QA76 Computer software
Al-Badri, Ayad H. Mousa
Developing Strategic Reports for National Co-Operative of Malaysia (Angkasa) Using Data Warehouse and Decision Tree Model
description Managing an organization requires access to information in order to monitor activities and assess performance. Business Intelligence (BI) solutions provide organizations with timley, itegrated information that is crucial to the understanding of their business. Data Warehouse (DW) technology is one of the important strategic management approaches for decision making in an organizations. The BI combines architectures, tools, databases, analytical tools, and methodologies to enable the implementation of interactive information in generating analytical reports. Strategic reports, which influence the enduring way of the whole company, are typically used by top managers. These kinds of decisions are repeatedly complex and the outcomes unsure, because existing information is habitually incomplete. Managers at this point must normally depend on history experiences and their instincts when making strategic decisions. DW is a technology allows integrating and transforming enterprise data for strategic decision making. Furthermore, Decision Tree (DT) is a decision support tool that uses a tree-like graphof decisions and their possible consequences, including chance event outcomes, resource costs, and utility. The organization, which is, responsible to manage people activities need strategic decisions making. This paper will be focused how to design and develop Strategic Reports using DW and DT Model for National Co-operative Organization of Malaysia (ANGKASA) called DSRNCO, as a case study. This system has been evaluated through the system user feedback by using Computer System Usability Questionnaire (CSUQ), which measures system usability and user satisfaction.
format Thesis
qualification_name masters
qualification_level Master's degree
author Al-Badri, Ayad H. Mousa
author_facet Al-Badri, Ayad H. Mousa
author_sort Al-Badri, Ayad H. Mousa
title Developing Strategic Reports for National Co-Operative of Malaysia (Angkasa) Using Data Warehouse and Decision Tree Model
title_short Developing Strategic Reports for National Co-Operative of Malaysia (Angkasa) Using Data Warehouse and Decision Tree Model
title_full Developing Strategic Reports for National Co-Operative of Malaysia (Angkasa) Using Data Warehouse and Decision Tree Model
title_fullStr Developing Strategic Reports for National Co-Operative of Malaysia (Angkasa) Using Data Warehouse and Decision Tree Model
title_full_unstemmed Developing Strategic Reports for National Co-Operative of Malaysia (Angkasa) Using Data Warehouse and Decision Tree Model
title_sort developing strategic reports for national co-operative of malaysia (angkasa) using data warehouse and decision tree model
granting_institution Universiti Utara Malaysia
granting_department Awang Had Salleh Graduate School of Arts & Sciences
publishDate 2012
url https://etd.uum.edu.my/2931/1/Ayad_H._Mousa_Al-Badri.pdf
https://etd.uum.edu.my/2931/2/Ayad_H._Mousa_Al-Badri-1.pdf
_version_ 1747827463813070848
spelling my-uum-etd.29312022-04-10T06:05:01Z Developing Strategic Reports for National Co-Operative of Malaysia (Angkasa) Using Data Warehouse and Decision Tree Model 2012-02 Al-Badri, Ayad H. Mousa Shiratuddin, Norshuhada Abu Bakar, Muhamad Shahbani Awang Had Salleh Graduate School of Arts & Sciences Awang Had Salleh Graduate School of Arts and Sciences QA76 Computer software Managing an organization requires access to information in order to monitor activities and assess performance. Business Intelligence (BI) solutions provide organizations with timley, itegrated information that is crucial to the understanding of their business. Data Warehouse (DW) technology is one of the important strategic management approaches for decision making in an organizations. The BI combines architectures, tools, databases, analytical tools, and methodologies to enable the implementation of interactive information in generating analytical reports. Strategic reports, which influence the enduring way of the whole company, are typically used by top managers. These kinds of decisions are repeatedly complex and the outcomes unsure, because existing information is habitually incomplete. Managers at this point must normally depend on history experiences and their instincts when making strategic decisions. DW is a technology allows integrating and transforming enterprise data for strategic decision making. Furthermore, Decision Tree (DT) is a decision support tool that uses a tree-like graphof decisions and their possible consequences, including chance event outcomes, resource costs, and utility. The organization, which is, responsible to manage people activities need strategic decisions making. This paper will be focused how to design and develop Strategic Reports using DW and DT Model for National Co-operative Organization of Malaysia (ANGKASA) called DSRNCO, as a case study. This system has been evaluated through the system user feedback by using Computer System Usability Questionnaire (CSUQ), which measures system usability and user satisfaction. 2012-02 Thesis https://etd.uum.edu.my/2931/ https://etd.uum.edu.my/2931/1/Ayad_H._Mousa_Al-Badri.pdf text eng public https://etd.uum.edu.my/2931/2/Ayad_H._Mousa_Al-Badri-1.pdf text eng public masters masters Universiti Utara Malaysia Apte C.,Lin B.,Pednault E. & Smyth P.(2002),Business Application of Data Mining Communication of ACM, vol.45,no 8,PP.49-53. Bruckner, R., List, B., & Schiefer, J. (2001). Developing requirements for data warehouse systems with use cases. Bresciani, P., Giorgini, P., Giunchiglia, F., Mylopoulos, J., & Perini, A. (2004). Tropos: An agent-oriented software development methodology. Journal of Autonomous Agents and Multi-Agent Systems, 8(3), 203–236. Balaceanu, D. (2007). Components of a Business Intelligence software solution.TotalSoft, 2(42).p5#. Beynon-Davies, P., Carne, C., Mackay, H., &Tudhope, D. (1999). Rapid application development (RAD): an empirical review. European Journal of Information Systems, 8(3), 211-223. Bruckner, R. M. (2007). Developing Requirements for Data Warehouse Systems with Use Cases. In Proceedings of Seventh Americas Conference on Information Systems, Data Management and Decision Support. Cleland, D. I., & King, W. R. (1983). Project Management Handbook. New York: Van Nostrand Reinhold Company Inc. Connolly, T., & Begg, C. (2010).Database Systems (5th ed.). United States of America: Pearson Education,Inc. Cooper, C. L., & Argyris, C. (1999).The Blackwell Eencyclopedic Dictionary of marketing (Vols. 4). Oxford, UK: Blackwell Publishers Ltd. Cousins, J., & Stewart, T. (2002). What is Business Process Design and Why Should ICare. UK: RivCom Ltd. Changjiang, L., Yufen, W., &Xiaojuan, G. (2010).The Application ResearchofOLAP in College Decision Support System.In Proceedings of Second International Conference on Multimedia and Information Technology, Kaifeng,China:IEEE. Chau, K. W., Cao, Y., Anson, M., & Zhang, J. (2003). Application of data warehouse and decision support system in construction management. Automation in construction,12(2), 213-224. Chaudhuri, S., Dayal, U., &Ganti, V. (2002). Database technology for decision support systems. Computer 34(12), 48-55. Chen, C., Xifeng, Y., Zhu, F., Jiawei, H., & Yu, P. S. (2008). Graph OLAP: Towards Online Analytical Processing on Graphs. In Proceedings of The Eighth International Conference on Data Mining, Pisa, Italy: IEEE. Eckerson, W. (2003).Understanding Business Intelligence.Retrieved Nov 6, 2010, from http://mis.dankook.ac.kr/jchoi/teaching/bi/understandbi.pdf. Exforsys.(2010). Designing the Dimensional Model and Preparing the data for OLAP. Retrieved January 7, 2011, from http://www.exforsys.com Firestone, J. M. (2003). Enterprise information portals and knowledge management. USA: Excutive Information Systems Inc. Folorunso, O., Ogunde, A. O., Vincent, R. O., & Salako, O. (2010). Data Mining for Business Intelligence in Distribution Chain Analytics. International Journal of the Computer, the Internet and Management, 18(1),15-26. Golfarelli, M., Rizzi, S., &Cella, L. (2004).Beyond Data Warehousing: What‘s next in-Business Intelligence? In Proceedings of DOLAP-04, Washington, DC, USA. Golfarelli, M. (2009). From User Requirements to Conceptual Design in Data Warehouse Design.Data warehousing design and advanced engineering applications: methods for complex construction, 1. Haselden, K. (2006) Microsoft SQL Server 2005 Integration Services (SQL Server Series)USA,Indianapolis: Sams. Heeks, R (2002). Information System and Development Countries:Failure ,Success and Local Information Society, 18(2) 101-112. Heise, D. L. (2005).Data Warehousing and Decision Making in Higher Education in the United States.Andrews University, Michigan. Hofreiter, B., &Huemer, C. (2002).B2B Integration - Aligning ebXML and Ontology Approaches. In Proceedings of EurAsia-ICT 2002:, Shiraz. Hua-long, Z. (2008).Applicationof OLAP to the analysis of the curriculum choosen by students. In Proceedings of The2nd International Conference on Anti-counterfeiting, Security and Identification, Guiyang,China:IEEE. Humphries, M., Hawkins, M. W., &Dy, M. C. (1999).Data Warehousing: Architecture and Implementation. New Jersey: Prentice-Hall,Inc. Inmon, W. H. (2002) Building the Data Warehouse. United States of America: John Wiley &Sons, Inc. John, T. (2007).Online Analytical Processing. Yeung, A. K. W., & Hall, G. B.(2007). Spatial Data Sharing, Data Warehousing and Database Federation.Spatial Database Systems, 175-216. Jorden, J. L. (2007). Mastering SQL Server 2005 Reporting Services Infrastrucure Design. Indiana: Wiley Publishing, Inc. Kimball, R., & Ross, M. (2002).The Data Warehouse Toolkit (2nd ed.). USA: Robert Ipsen. Kimball, R., Ross, M., Thornwaite, W., Mundy, J., & Becker, B. (2008).The Data WarehouseLifecycle Toolkit: Expert Methods for Designing, Developing and DeployingData Warehouse. New York: Wiley Computer Publishing. Kress, M., Mostaghim, S., &Seese, D. (2009). Intelligent Business Process Execution using Particle Swarm Optimization. Nature-Inspired Informatics for Intelligent Applications and Knowledge Discovery: Implications in Business, Science, and Engineering, 49-55. Lemire, D. (2007). Data Warehousing and OLAP: A Research-Oriented Bibliography. Retrieved January 8, 2011, from http://www.daniel-lemire.com/OLAP/ Lewis, J. R. (1995). IBM Computer Usability Satisfaction Questionnaires: Psychometric Evaluation and Instructions for Use. International Journal for Human-Computer Interaction, 7(1), 57-78. Lisin, M., & Joseph, J. (2006) Microsoft SQL Server 2005 Reporting Services (SQL ServerSeries). USA,Indianapolis: Sams. Li, X., Qu, H., Zhu, Z., & Han, Y. (2009).A Systematic Information Collection Method for Business Intelligence.In Proceedings of International Conference on Electronic Commerce and Business Intelligence, Beijing. MacLennan, Z. T. (2007). Data Mining with SQL Server 2005.Crosspoint Boulevard: Wiley Publishing. Malinowski, E., &Zimányi, E. (2006). Hierarchies in a multidimensional model:FromConceptualmodeling tological representation. Data & KnowledgeEngineering 59(2), 348-377. McFadden, F. R. (1996).Data warehouse for EIS: some issues and impacts.In Proceedings of the Twenty-Ninth International Conference on System Sciences,Hawaii, USA:IEEE. Nestorov, S., & Jukić, N. (2002). Ad-Hoc Association-Rule Mining within the Data Warehouse. In Proceedings of the 36thInternational Conference on System Sciences (HICSS’03), (p.10-13). Hawaii. Olszak, C. M., &Ziemba, E. (2003).Business Intelligence as a Key to Management of an Enterprise.In Proceedings of Informing Science+ Information Technology Education. Pori, Finland:InSITE. Qiang, G., Lirong, W., Qiaofeng, Z., &Ranran, F. (2010).Method used to construct the marketing channel analysis system of a company of ShanDong branch '10: of China Mobile based on data warehouse technology. In Proceedings of International Conference on Educational and InformationTechnology, Chongqing, China:IEEE. Romero, C., & Ventura, S. (2007). Educational data mining: A survey from 1995 to 2005. Expert Systems with Applications, 33(1), 135-146. Sahama, T. R., & Croll, P. R. (2007). A data warehouse architecture for clinical data warehousing. Seify, M. (2010). Importance of KPI in BI System, Case Study: Iranian Industries. In Proceedings of the Seventh International Conference on Information Technology: New Generations (ITNG), Las Vegas, NV: IEEE. Sinclair, D., &Zairi, M. (1995). Effective process management through performance measurement: Part III- An integrated model of total quality-based performance measurement. Business Process Management Journal,1(3),50-65. Sol, H. G., Takkenberg, A. Th., C., &Robbé, d. V. (1985). Expert systems and artificialintelligence in decision support systems. In Proceedings of second Mini Euroconference,Lunteren, Netherlands. Surajit, C., &Umeshwar, D. (1997) An overview of data warehousing and OLAP technology.SIGMOD Rec. 26(1), 65-74. Shahbani, M., & Shiratuddin, N., (2009). Community and Approach Using Requirement Centric Operational Data Store (ReCODS) Model For Business Intelligence Applications. In Proceedings of WSEAS3rd International Conference, Greece. Shahbani, M., &Shiratuddin, N., (2011).Conceptual Design Model Using Operational DataStore(CoDMODS) for Developing Business Intelligence Applications.International Journal of Computer Science and Network Security (IJCSNS), VOL.11No.3,March 2011 Tang, J., Cui, K., Feng, Y., & Tong, G. (2009) The Research & Application of ETL Tool in Business Intelligence Project. In Proceedings of International Forum on Information Technology and Applications, Chengdu, China: IEEE. Tong, G., Cui, K., & Song, B. (2008).The research & application of BusinessIntelligence system in retail industry. In Proceedings of International Conference on Automation and Logistics, Qingdao,China:IEEE. Turban E., Rainer R.K. & Potter R.E. (2005). Introduction to Information Technology (3rd Edition). New Jersey: John Wiley & Sons Inc. Venkatadri, M., Hanumat, G. S., & Manjunath, G. (2010). A Novel Business Intelligence System Framework.Universal Journal of Computer Science and Engineering Technology, 1(2),112-116. Ventura, C. R. (2006). Educational data mining: A survey from 1995 to 2005. Expert Systems with Applications ,33 (2007), 135–146 , 13. Weiss, G. (2009). Data Mining in the Telecommunications Industry.Encyclopedia of Data Warehousing and Mining, 2(1), 486-487. Wolte, J. (1998). Information Pyramids Compactly Visualising Large Hierarchies. Graz University of Technology, Graz, Austria. Wrembel, R., &Koncilia, C. (2007).Data warehouses and OLAP: Concepts, Achitectures, and Solutions. USA: Idea Group Inc. Xiaofei, Z., &Zhiqiu, H. (2010).A quality evaluation approach for OLAP metadata of multidimensional OLAPdata. In Proceedings of the 2nd International Conference on Information Management and Engineering, Chengdu, China: IEEE. Yeung, A. K. W., & Hall, G. B. (2007). Spatial Data Sharing, Data Warehousing and Database Federation. Spatial Database Systems, 175-216. Zhang, D.P. (2009) A Data Warehouse Based on University Human Resource Management of Performance Evaluation. In Proceedings of the International Forum on Information Technology and Applications, Chengdu,China:IEEE. Zubcoff, J., & Trujillo, J. (2007). A UML 2.0 profile to design Association Rule mining models in the multidimensional conceptual modeling of data warehouses. Data & Knowledge Engineering, 63(1), 44-62.