The Experts below are selected from a list of 312 Experts worldwide ranked by ideXlab platform
S Chowdhury - One of the best experts on this subject based on the ideXlab platform.
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HICSS - Best practices in data warehousing to support business initiatives and needs
37th Annual Hawaii International Conference on System Sciences 2004. Proceedings of the, 2004Co-Authors: Justin Lawyer, S ChowdhuryAbstract:The paper presents the data warehousing architecture and practices used at a major U. S. retailing company. Many considerations were assessed when deciding which data warehousing architecture to adopt. The paper discusses the two pre-dominant styles in data warehousing, namely the "Bill Inmon Style" or the top-down approach and the "Ralph Kimball Style "or the bottom-up approach. The company chose the Inmon style due to a unique combination of circumstances in their business and technical environments, which are being discussed in detail. Much of the information presented in this paper is based upon the direct experiences of the lead data architect assigned to the projects under which this U. S. retailing company's Customer data warehouse evolved. The architecture has evolved over time and currently has been accepted at the company as a best practice. It is interesting to mention that both the hardware platform (CPU and disk drives) and relational database management system (RDBMS) software employed today at this company for data warehousing is not the same as was selected for the first instantiation. The implication was that the best plan or practice was a flexible one. There were many challenges, like organizational, technical, data sourcing and data naming, needed to be solved during the pre-project, initial stages, and throughout the project and beyond. The initial data warehouse, implemented in 1996, was termed an overall success and approved for expansion. The current data warehouse data are being used by over six hundred registered users to fine-tune Customer marketing and leverage and share data in an Enterprise manner. The data warehouse has allowed the company to strengthen Customer relationship management (CRM) core capabilities and business partnerships. Today, there are many departments benefiting from queries and requests for data warehouse data, many anticipated, some not. Although not planned, the data warehouse has been a valuable source of purchase and Customer data in case of a manufacturer recall of merchandise. Above all, the company has been able to leverage and share Enterprise Customer data to the benefit of the entire company.
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Best practices in data warehousing to support business initiatives and needs
37th Annual Hawaii International Conference on System Sciences 2004. Proceedings of the, 2004Co-Authors: Justin Lawyer, S ChowdhuryAbstract:The paper presents the data warehousing architecture and practices used at a major U. S. retailing company. Many considerations were assessed when deciding which data warehousing architecture to adopt. The paper discusses the two pre-dominant styles in data warehousing, namely the "Bill Inmon Style" or the top-down approach and the "Ralph Kimball Style "or the bottom-up approach. The company chose the Inmon style due to a unique combination of circumstances in their business and technical environments, which are being discussed in detail. Much of the information presented in this paper is based upon the direct experiences of the lead data architect assigned to the projects under which this U. S. retailing company's Customer data warehouse evolved. The architecture has evolved over time and currently has been accepted at the company as a best practice. It is interesting to mention that both the hardware platform (CPU and disk drives) and relational database management system (RDBMS) software employed today at this company for data warehousing is not the same as was selected for the first instantiation. The implication was that the best plan or practice was a flexible one. There were many challenges, like organizational, technical, data sourcing and data naming, needed to be solved during the pre-project, initial stages, and throughout the project and beyond. The initial data warehouse, implemented in 1996, was termed an overall success and approved for expansion. The current data warehouse data are being used by over six hundred registered users to fine-tune Customer marketing and leverage and share data in an Enterprise manner. The data warehouse has allowed the company to strengthen Customer relationship management (CRM) core capabilities and business partnerships. Today, there are many departments benefiting from queries and requests for data warehouse data, many anticipated, some not. Although not planned, the data warehouse has been a valuable source of purchase and Customer data in case of a manufacturer recall of merchandise. Above all, the company has been able to leverage and share Enterprise Customer data to the benefit of the entire company.
Ayong Li - One of the best experts on this subject based on the ideXlab platform.
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Notice of Retraction: Research on iron and steel Enterprise Customer satisfaction evaluation based on unascertained theory
2013 International Conference on Quality Reliability Risk Maintenance and Safety Engineering (QR2MSE), 2013Co-Authors: Xiang Wang, Ayong LiAbstract:This article has been retracted by the publisher.
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Notice of Retraction Research on iron and steel Enterprise Customer satisfaction evaluation based on unascertained theory
2013 International Conference on Quality Reliability Risk Maintenance and Safety Engineering (QR2MSE), 2013Co-Authors: Xiang Wang, Ayong LiAbstract:This research devises an index system of evaluating iron and steel Enterprise Customer satisfaction on the basis of summarizing Customer satisfaction theories, in view of current characteristics of the iron and steel Enterprises in China and by means of adopting indices to Customer satisfaction evaluation. An iron and steel Enterprise Customer satisfaction evaluation model based on unascertained theory is constructed and applied to a certain iron and steel Enterprise. The results of this Enterprise's Customer satisfaction are obtained through analyzing the statistics from questionnaire design and survey in the Enterprise. According to the results, this paper puts forward suggestions for its improvement.
Justin Lawyer - One of the best experts on this subject based on the ideXlab platform.
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HICSS - Best practices in data warehousing to support business initiatives and needs
37th Annual Hawaii International Conference on System Sciences 2004. Proceedings of the, 2004Co-Authors: Justin Lawyer, S ChowdhuryAbstract:The paper presents the data warehousing architecture and practices used at a major U. S. retailing company. Many considerations were assessed when deciding which data warehousing architecture to adopt. The paper discusses the two pre-dominant styles in data warehousing, namely the "Bill Inmon Style" or the top-down approach and the "Ralph Kimball Style "or the bottom-up approach. The company chose the Inmon style due to a unique combination of circumstances in their business and technical environments, which are being discussed in detail. Much of the information presented in this paper is based upon the direct experiences of the lead data architect assigned to the projects under which this U. S. retailing company's Customer data warehouse evolved. The architecture has evolved over time and currently has been accepted at the company as a best practice. It is interesting to mention that both the hardware platform (CPU and disk drives) and relational database management system (RDBMS) software employed today at this company for data warehousing is not the same as was selected for the first instantiation. The implication was that the best plan or practice was a flexible one. There were many challenges, like organizational, technical, data sourcing and data naming, needed to be solved during the pre-project, initial stages, and throughout the project and beyond. The initial data warehouse, implemented in 1996, was termed an overall success and approved for expansion. The current data warehouse data are being used by over six hundred registered users to fine-tune Customer marketing and leverage and share data in an Enterprise manner. The data warehouse has allowed the company to strengthen Customer relationship management (CRM) core capabilities and business partnerships. Today, there are many departments benefiting from queries and requests for data warehouse data, many anticipated, some not. Although not planned, the data warehouse has been a valuable source of purchase and Customer data in case of a manufacturer recall of merchandise. Above all, the company has been able to leverage and share Enterprise Customer data to the benefit of the entire company.
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Best practices in data warehousing to support business initiatives and needs
37th Annual Hawaii International Conference on System Sciences 2004. Proceedings of the, 2004Co-Authors: Justin Lawyer, S ChowdhuryAbstract:The paper presents the data warehousing architecture and practices used at a major U. S. retailing company. Many considerations were assessed when deciding which data warehousing architecture to adopt. The paper discusses the two pre-dominant styles in data warehousing, namely the "Bill Inmon Style" or the top-down approach and the "Ralph Kimball Style "or the bottom-up approach. The company chose the Inmon style due to a unique combination of circumstances in their business and technical environments, which are being discussed in detail. Much of the information presented in this paper is based upon the direct experiences of the lead data architect assigned to the projects under which this U. S. retailing company's Customer data warehouse evolved. The architecture has evolved over time and currently has been accepted at the company as a best practice. It is interesting to mention that both the hardware platform (CPU and disk drives) and relational database management system (RDBMS) software employed today at this company for data warehousing is not the same as was selected for the first instantiation. The implication was that the best plan or practice was a flexible one. There were many challenges, like organizational, technical, data sourcing and data naming, needed to be solved during the pre-project, initial stages, and throughout the project and beyond. The initial data warehouse, implemented in 1996, was termed an overall success and approved for expansion. The current data warehouse data are being used by over six hundred registered users to fine-tune Customer marketing and leverage and share data in an Enterprise manner. The data warehouse has allowed the company to strengthen Customer relationship management (CRM) core capabilities and business partnerships. Today, there are many departments benefiting from queries and requests for data warehouse data, many anticipated, some not. Although not planned, the data warehouse has been a valuable source of purchase and Customer data in case of a manufacturer recall of merchandise. Above all, the company has been able to leverage and share Enterprise Customer data to the benefit of the entire company.
Liu Xiang - One of the best experts on this subject based on the ideXlab platform.
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a new Enterprise Customer and supplier cooperative system framework based on multiple criteria decision making
International Conference on Systems, 2008Co-Authors: Liu XiangAbstract:An Enterprise Customer and supplier cooperative system is powerful tools to solving Customer and supplier multiple criteria decision-making (MCDM) problems. This study develops an agent-based and service-oriented Enterprise Customer and supplier cooperative system framework based on multiple criteria decision-making. It consists of three main components. The first component is Customer and supplier group decision-making (GDM) approach in which many participants' points of views are considered in the modeling of a specific problem. In the second component, a new approach for solving Enterprise Customer and supplier MCDM problems is proposed based on cooperative neural network. The third component is related to Enterprise Customer and supplier MCDM cooperative intelligent system that are supported by new technologies such as multi-agent, multi-dimensional query expression for document warehouses, distributed data mining, cooperative neural network . A new software system called Enterprise Customer and supplier cooperative system is developed based on the framework. Enterprise Customer and supplier cooperative system can be accessed from Web. The software provides online queries, and online analysis functions for users anywhere at any time. An example of the software as tested on Enterprise Customer and supplier MCDM problems is presented to illustrate its effectiveness.
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ICONS - A New Enterprise Customer and Supplier Cooperative System Framework Based on Multiple Criteria Decision-Making
Third International Conference on Systems (icons 2008), 2008Co-Authors: Liu XiangAbstract:An Enterprise Customer and supplier cooperative system is powerful tools to solving Customer and supplier multiple criteria decision-making (MCDM) problems. This study develops an agent-based and service-oriented Enterprise Customer and supplier cooperative system framework based on multiple criteria decision-making. It consists of three main components. The first component is Customer and supplier group decision-making (GDM) approach in which many participants' points of views are considered in the modeling of a specific problem. In the second component, a new approach for solving Enterprise Customer and supplier MCDM problems is proposed based on cooperative neural network. The third component is related to Enterprise Customer and supplier MCDM cooperative intelligent system that are supported by new technologies such as multi-agent, multi-dimensional query expression for document warehouses, distributed data mining, cooperative neural network . A new software system called Enterprise Customer and supplier cooperative system is developed based on the framework. Enterprise Customer and supplier cooperative system can be accessed from Web. The software provides online queries, and online analysis functions for users anywhere at any time. An example of the software as tested on Enterprise Customer and supplier MCDM problems is presented to illustrate its effectiveness.
Xiang Wang - One of the best experts on this subject based on the ideXlab platform.
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Notice of Retraction: Research on iron and steel Enterprise Customer satisfaction evaluation based on unascertained theory
2013 International Conference on Quality Reliability Risk Maintenance and Safety Engineering (QR2MSE), 2013Co-Authors: Xiang Wang, Ayong LiAbstract:This article has been retracted by the publisher.
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Notice of Retraction Research on iron and steel Enterprise Customer satisfaction evaluation based on unascertained theory
2013 International Conference on Quality Reliability Risk Maintenance and Safety Engineering (QR2MSE), 2013Co-Authors: Xiang Wang, Ayong LiAbstract:This research devises an index system of evaluating iron and steel Enterprise Customer satisfaction on the basis of summarizing Customer satisfaction theories, in view of current characteristics of the iron and steel Enterprises in China and by means of adopting indices to Customer satisfaction evaluation. An iron and steel Enterprise Customer satisfaction evaluation model based on unascertained theory is constructed and applied to a certain iron and steel Enterprise. The results of this Enterprise's Customer satisfaction are obtained through analyzing the statistics from questionnaire design and survey in the Enterprise. According to the results, this paper puts forward suggestions for its improvement.
