Title page for etd-0806101-104235


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URN etd-0806101-104235
Author Tzu-Chao Tsai
Author's Email Address tctsai@ms5.url.com.tw
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Department Information Management
Year 2000
Semester 2
Degree Master
Type of Document
Language English
Title Supporting Data Warehouse Design with Data Mining Approach
Date of Defense 2001-07-23
Page Count 75
Keyword
  • Hierarchical Agglomerative Clustering Technique
  • Data Mining
  • Data Warehouse
  • Knowledge Discovery
  • Data Warehouse Design
  • Star Schema
  • Abstract Traditional relational database model does not have enough capability to cope with a great deal of data in finite time. To address these requirements, data warehouses and online analytical processing (OLAP) have emerged. Data warehouses improve the productivity of corporate decision makers through consolidation, conversion, transformation, and integration of operational data, and supports online analytical processing (OLAP). The data warehouse design is a complex and knowledge intensive process. It needs to consider not only the structure of the underlying operational databases (source-driven), but also the information requirements of decision makers (user-driven). Past research focused predominately on supporting the source-driven data warehouse design process, but paid less attention to supporting the user-driven data warehouse design process. Thus, the goal of this research is to propose a user-driven data warehouse design support system based on the knowledge discovery approach. Specifically, a Data Warehouse Design Support System was proposed and the generalization hierarchy and generalized star schemas were used as the data warehouse design knowledge. The technique for learning these design knowledge and reasoning upon them were developed. An empirical evaluation study was conducted to validate the effectiveness on the proposed techniques in supporting data warehouse design process. The result of empirical evaluation showed that this technique was useful to support data warehouse design especially on reducing the missing design and enhancing the potentially useful design.
    Advisory Committee
  • Fu-Ren Lin - chair
  • Sheng-Tun Li - co-chair
  • Chih-Ping Wei - advisor
  • Files
  • etd-0806101-104235.pdf
  • indicate access worldwide
    Date of Submission 2001-08-06

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