Web based business intelligence to support supply chain operations

Today’s supply chain management is facing big challenges; the volume of information flowing into the organizations from various sources is growing. Therefore, an effective solution to provide decision-makers with timely insights and predictive analytics is needed in today’s competitive market. Da...

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Main Author: Li, Ang.
Other Authors: Huang Guangbin
Format: Final Year Project
Language:English
Published: 2013
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Online Access:http://hdl.handle.net/10356/53352
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-533522023-07-07T16:45:28Z Web based business intelligence to support supply chain operations Li, Ang. Huang Guangbin School of Electrical and Electronic Engineering Yan Wenjing DRNTU::Engineering Today’s supply chain management is facing big challenges; the volume of information flowing into the organizations from various sources is growing. Therefore, an effective solution to provide decision-makers with timely insights and predictive analytics is needed in today’s competitive market. Data mining, a powerful business intelligence tool, has showed great effects on data analytics and trend prediction in different industries. This report discusses the application of Association Rule Mining Technique (a popular data mining technique) on pattern identification and information extraction in supply chain management. Meanwhile, a web-based application is designed and implemented to find meaningful patterns in large supply chain database as well. The main content of this report is divided into three parts. Basic supply chain management knowledge and different data mining techniques are introduced in Background Knowledge of the report; this section also explains how data mining techniques solve constrains in supply chain management theoretically. Application Design, the second part of main content, focuses on Association Rule Mining (ARM) Techniques and detailed algorithms of three important ARM (Apriori, FP Tree and Matrix Apriori) implemented in this application. Pseudo code, example demonstrations and advantages/disadvantages analysis of each technique are included in this section to provide audience a clear understanding. Application Results, the last part of main content, starts by introducing all the tools and programming languages used to develop web application including Microsoft Visual Studio, ASP.NET framework, C# and HTML. It then demonstrates the detailed structure of this application including designs of graphical user interfaces, functional business process designs and special data representation functionalities. Bachelor of Engineering 2013-05-31T07:58:27Z 2013-05-31T07:58:27Z 2013 2013 Final Year Project (FYP) http://hdl.handle.net/10356/53352 en Nanyang Technological University 98 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering
spellingShingle DRNTU::Engineering
Li, Ang.
Web based business intelligence to support supply chain operations
description Today’s supply chain management is facing big challenges; the volume of information flowing into the organizations from various sources is growing. Therefore, an effective solution to provide decision-makers with timely insights and predictive analytics is needed in today’s competitive market. Data mining, a powerful business intelligence tool, has showed great effects on data analytics and trend prediction in different industries. This report discusses the application of Association Rule Mining Technique (a popular data mining technique) on pattern identification and information extraction in supply chain management. Meanwhile, a web-based application is designed and implemented to find meaningful patterns in large supply chain database as well. The main content of this report is divided into three parts. Basic supply chain management knowledge and different data mining techniques are introduced in Background Knowledge of the report; this section also explains how data mining techniques solve constrains in supply chain management theoretically. Application Design, the second part of main content, focuses on Association Rule Mining (ARM) Techniques and detailed algorithms of three important ARM (Apriori, FP Tree and Matrix Apriori) implemented in this application. Pseudo code, example demonstrations and advantages/disadvantages analysis of each technique are included in this section to provide audience a clear understanding. Application Results, the last part of main content, starts by introducing all the tools and programming languages used to develop web application including Microsoft Visual Studio, ASP.NET framework, C# and HTML. It then demonstrates the detailed structure of this application including designs of graphical user interfaces, functional business process designs and special data representation functionalities.
author2 Huang Guangbin
author_facet Huang Guangbin
Li, Ang.
format Final Year Project
author Li, Ang.
author_sort Li, Ang.
title Web based business intelligence to support supply chain operations
title_short Web based business intelligence to support supply chain operations
title_full Web based business intelligence to support supply chain operations
title_fullStr Web based business intelligence to support supply chain operations
title_full_unstemmed Web based business intelligence to support supply chain operations
title_sort web based business intelligence to support supply chain operations
publishDate 2013
url http://hdl.handle.net/10356/53352
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