Design Principles and Methods for Distributed Business Intelligence Ecosystem

Валентин Кисимов; Камелия Стефанова

doi:10.37075/RP.2010.1.06

Authors

Assoc. Prof. Dr Valentin Kisimov Department of Information Technologies and Communications, Faculty of Applied Informatics and Statistics, UNWE Author
Assoc. Prof. Dr Kamelia Stefanova Department of Information Technologies and Communications, Faculty of Applied Informatics and Statistics, UNWE Author

DOI:

https://doi.org/10.37075/RP.2010.1.06

Abstract

The paper is dedicated to a new approach in the scientific research, oriented towards Distributed Business Intelligent Ecosystems. This system is designed based on Distributed Business Intelligence Competence Centre. For the needs of Small and Medium Enterprises, the system is designed as a distributed. Three principles of distribution are presented – Principle of Horizontal distribution, Principle of Vertical distribution and the principle of Embedded distribution. A Design Framework is created on their basis, for the purpose of design of the following methods – Method for distribution of Data Warehouses, Method for distribution of OLAP engines, Method for distribution of Data Mining engines, and Method for distribution of Dashboards.

References

Codd, E. F., Codd, S. B., & Salley, C. T. (1993). Providing OLAP to User-analysts: An IT Mandate. Medical Entomology and Zoology. URL: http://www.fpm.com/refer/codd.html

Lyman, P. & Varian, H. (2009). P. Lyman, H. Varian, How much information?. URL: http://www2.sims.berkeley.edu/research/projects/how-much-info-2003/ (accessed 2009-12-10)

S. Few (2004). Dashboard confusion. Intelligent Enterprise, 4. URL: http://www.intelligententerprise.com/showArticle.jhtml?articleID=18300136 (accessed 2009-10-04)

Mark Rittman, Building BI Dashboards with Oracle Database, Oracle Discoverer, and Oracle Portal. (2008). URL: http://www.oracle.com/technology/pub/articles/rittman_dash.html (accessed 2010-05-04)

IBM Information Server architecture and concepts. (2008). URL: http://publib.boulder.ibm.com/infocenter/iisinfsv/v8r0/index.jsp?topic=/com.ibm.swg.im.iis.productization.iisinfsv.overview.doc/topics/cisoarchoverview.html (accessed 2009-07-30)

L. Mustatea (2004). Creating a Distributed Data Warehouse for Effective Workload Balancing and Data Sharing. TDW, 18. URL: http://www.tdwi.org/Publications/WhatWorks/display.aspx?id=7316 (accessed 2009-10-04)

Akinde, Michael O., Böhlen, Michael H., Johnson, Theodore, Lakshmanan, Laks V.S., & Srivastava, Divesh (2002). Efficient OLAP query processing in distributed data warehouses. Information Systems. DOI: https://doi.org/10.1016/S0306-4379(02)00051-0

R. Moeler (2000). Distributed Data warehousing using Web technology. AMACOM. ISBN: 0-8144-0588-6

Qiming, C., Jie, D., Umeshwar, D., & Meichun, H. (2006). Distributed OLAP-based association rule generation method and system. USA Patent 7007020.

Chen, Q. & Dayal, U. (2004). A Distributed OLAP Infrastructure for E-Commerce. Proceedings Fourth IFCIS International Conference on Cooperative Information Systems. CoopIS 99 (Cat. No.PR00384), 209-220. DOI: https://doi.org/10.1109/COOPIS.1999.792171

Zaki, J. & Pan, Y. (2002). Special Issue on Parallel and Distributed Data Mining. International Journal of Distributed and Parallel Databases, 11(2), 123-127. DOI: https://doi.org/10.1023/A:1013918601668

D. Talia (2006). Grid-based Distributed Data mining systems, Algorithms and Services. University of Calabria, Italy. URL: http://www.siam.org/meetings/sdm06/workproceed/HPDM/Domenico_talia_Invited_Session.pdf (accessed 2009-11-30)

Clifton, C., Wenliang, K., & Atallah, M. (2009). Distributer Data Mining to protect Information Privacy. URL: http://www.cs.purdue.edu/homes/clifton/DistDM/ppddm_nsf.pdf (accessed 2010-05-01)

Clifton, C., Wagstaff, K. W., & Atallah, M. (2009). Distributed Data Mining to Protect Information Privacy. URL: http://www.cs.purdue.edu/homes/clifton/DistDM/ppddm_nsf.pdf (accessed 2009-08-20)

PA Consulting Group (2007). Business Intelligence Competency Centre: Deliver a step change in your performance management by establishing a Business Intelligence Competency Centre. URL: www.paconsulting.com (accessed 2010-02-04)

White Paper: Business Intelligence Competency Centers: Creating a successful business intelligence strategy. (2006). URL: www.sas.com (accessed 2009-09-06)