摘要(英) |
The data warehouse performance has always been an important and challenged task For MIS (Management Information System) department, Due to theist scale, it has always been difficult to tune data warehouse performance, especially in the enterprise level. This research aims at providing a solution based on skills of knowledge management to improve the data warehouse tuning. This research collected many verified performance tuning knowledge and expert experiences, then organize them into a suitable knowledge structure, and finally create a knowledge management system.
This research divides the performance tuning knowledge into several high level subjects based on the different sources that the performance problems result from. They include, at least,“Operating System,”“Database Management System,”“Dynamic Report,”“Ad Hoc Query” and “Batch Job.” Able to organize and share the knowledge allows all users and/or system administrators to easily find the suitable knowledge or experience for their cases on hand. This also encourage them to further contribute their expertise and experiences after benefiting from ths knowledge management systems.
This research also tries to quantify some of the knowledge case in order to use the raw data from real-time “Performance Monitor System” to create a real-time knowledge recommendation system for potential problems occurring in enterprise data warehouse. When some potential performance issues occur, the quantification condition associated with knowledge case is automatically matched with the data from real-time “Performance Monitor System.” This may determine problem and warn related persons to give them some suggestion action based on the knowledge in the knowledge systems. This peculiar design feature has never seen before in knowledge management system. It is a feasible solution, because about 80% jobs were duplicated in data warehouse. |
參考文獻 |
參考文獻
英文部分
1. Geoff Ingram, High-Performance Oracle, Wiley Publishing, Inc., United States of America, 2002.
2. William H. Inmon, Ken Rudin, Christopher K. Buss, Ryan Sousa, Data Warehouse Performance, Jonh Wiley&Sons, Inc., United States of America, 1999.
3. William H. Inmon, Building the Data Warehouse, Fourth Edition, Wiley Publishing, Inc., United States of America, 2005.
4. Kimball, Ralph, Laura Reeves, Margy Ross, and Warren Thornthwaite, The Data Warehouse Lifecycle Toolkit, John Wiley&Sons, Inc., New York, 1998.
5. Paulraj Ponniah, Data Warehousing Fundamentals, Jonh Wiley&Sons, Inc., United States of America, 2001.
6. Matthias Jarke, Maurizio Lenzerini, Yannis Vassiliou, Panos Vassiliadis, Fundamentals of Data Warehouses, Second Edition, Springer-Verlag Berlin Heidelberg, Germany,2000.
7. Jonathan Lewis, Cost-Based Oracle Fundamentals, Springer-Verlag New York, Inc., New York, 2006.
8. Donald Keith Burleson, Oracle High-Performance Tuning with STATSPACK, 潘得龍譯, Oracle 高效能調校—STATSPACK工具篇, McGraw-Hill, Inc., 2001.
9. Donald Keith Burleson, Oracle High-Performance SQL Tuning, 張裕益譯, Oracle 高效能SQL調校指南, McGraw-Hill, Inc., 2001.
10. Sumit Sarin, Oracle DBA Tips & Techniques, 陳佳鴻譯, Oracle DBA要訣經典, McGraw-Hill, Inc., 2000.
11. Davenport, T., De Long, D. & Beers, M., Successful Knowledge Management
Projects, Sloan Management Review, 1998
中文部分
12. 尤克強,知識管理與創新,天下遠見出版股份有限公司,台北市,民國90年。
13. 勤業管理顧問公司,知識管理的第一本書,商周,台北市,民國89年。
14. 碩網資訊,知識管理實務—SmartKMS軟體在知識管理的實做與應用,科技圖書股份有限公司,台北市,民國92年。
15. 黃廷合&吳思達,知識管理理論與實務,全華科技圖書股份有限公司,台北市,民國93年。
16. 伍忠賢&王建彬,知識管理:策略與實務,聯經出版事業公司,台北市,民國90年。
17. 黃麒祐編著,IT知識管理導論,文魁資訊股份有限公司,台北市,民國92年。
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網路資料部分
19. 網路資料:Tim Gorman:Tuning the Data Warehouse According to its Usage:
Usage Tracking in Decision-Support Systems. 2007年4月26日,取自http://www.evdbt.com/DwUsage.pdf
20. 網路資料:Andrew Holdsworth:Data Warehouse Performance Management Techniques. 2007年2月9日,取自
https://www.indiana.edu/~dbateam/resources/tips/dwperf.pdf
21. 網路資料:Bernhard Atzenberger, Marcus Bender:DWH Performance Enhancements with oracle9i 2001年4月,取自
http://www.oracle.com/technology/products/oracle9i/pdf/o9i_dwperfcomp_dwflow.pdf
22. 網路資料:李鑫:新一代資料倉儲的五大趨勢。 2004年4月14日,取自http://office.digitimes.com.tw/ShowNews.aspx?zCatId=15C&zNotesDocId=0933A6E3A68B94C948256D0500411F77
23. 網路資料:營建研發小組:知識地圖展現型態分類。 2004年,取自http://ckm.caece.net/codexml/2004/Map2.htm |