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Reseach Article

An approach to Construct the Fuzzy Data Mart using Soft Computing

by A. Prema, A. Pethalakshmi
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 58 - Number 20
Year of Publication: 2012
Authors: A. Prema, A. Pethalakshmi

A. Prema, A. Pethalakshmi . An approach to Construct the Fuzzy Data Mart using Soft Computing. International Journal of Computer Applications. 58, 20 ( November 2012), 29-32. DOI=10.5120/9399-3580

@article{ 10.5120/9399-3580,
author = { A. Prema, A. Pethalakshmi },
title = { An approach to Construct the Fuzzy Data Mart using Soft Computing },
journal = { International Journal of Computer Applications },
issue_date = { November 2012 },
volume = { 58 },
number = { 20 },
month = { November },
year = { 2012 },
issn = { 0975-8887 },
pages = { 29-32 },
numpages = {9},
url = { },
doi = { 10.5120/9399-3580 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
%0 Journal Article
%1 2024-02-06T21:03:01.791396+05:30
%A A. Prema
%A A. Pethalakshmi
%T An approach to Construct the Fuzzy Data Mart using Soft Computing
%J International Journal of Computer Applications
%@ 0975-8887
%V 58
%N 20
%P 29-32
%D 2012
%I Foundation of Computer Science (FCS), NY, USA

Data Mart is emerging as one of the hottest areas of growth in global business and the critical components and tool for business intelligence. A data mart is a local data warehouse used for storing business oriented information for future analysis and decision-making. In business scenarios, where some of the data are fuzzy, it may be effective to construct a warehouse that can strengthen the analysis of fuzzy data. This paper presents a Fuzzy Data Mart model that imparts the exile interface to the users and also extends the DWs for storing and managing the fuzzy data along with the crisp data records. We have proposed, an algorithm to design data mart, which improves the decision making processes. To do so, we use Extraction, Transformation and Load (ETL) tools for better performance. In addition to that, the membership function of fuzzy is used for summarization.

  1. H. -J. Lenz and A. Shoshani. "Summarizability in olap and statistical data bases". Statistical and Scientific Database Management, 1997.
  2. R. Kimball and M. Ross. "The Data Warehouse Toolkit. " WileyPublishing, Inc. , 2002.
  3. D. P´erez, M. J. Somodevilla, and I. H. Pineda. "Fuzzy spatial data warehouse: A multidimensional model. " Eighth Mexican International Conference on Current Trends in Computer Science, 2007.
  4. W. H. Inmon. " Building the Data Warehouse". Wiley Publishing,Inc. , 4 edition, 2005.
  5. M. Delgado, C. Molina, D. Sanchez, A. Vila, andL. Rodriguez-Ariza. "A fuzzy multidimensional model for supporting imprecision in OLAP". 2004 IEEE International Conference on Fuzzy Systems, 3:1331 – 1336, 2004.
  6. D. Fasel and D. Zumstein. „A fuzzy data warehouse approach for web analytics. "In M. D. Lytras, E. Damiani, J. M. Carroll, R. D. Tennyson, D. Avison, A. Naeve, A. Dale, P. Lefrere,F. Tan, J. Sipior, and G. Vossen, editors, Visioning and Engineering the Knowledge Society – AWeb Science Perspective,volume 5736 of Lecture Notes in Computer Science, pages 276–285. Springer, 2009.
  7. H. -J. Zimmermann. " Fuzzy Set Theory and its applications. "Kluwer Academic Publishers, 1991.
  8. Inmon, William (2000-07-18). "Data Mart Does Not Equal Data Warehouse". DMReview. com.
  9. Li Jian and Xu Bihua-" ETL Tool Research and Implementation Based on Drilling Data Warehouse "by,Southwest Petroleum University,Chengdu, China
  10. Ilovici, Lior Sapir,Armin Shm ". A methodology for the design of a Fuzzy Data Warehouse".
  11. Daniel Fasel,"A DataWarehouse Model for Integrating Fuzzy Concepts in Meta Table Structures" Information System Research Group,Department of Informatics,University of Fribourg , Switzerland .
  12. Powerful Techniques for High-Performance Data Warehousing
  13. G. T. S. Ho, K. L. Choy, T. C. Poon," Providing decision support functionality in warehouse management using the RFID-based fuzzy association rule mining approach "
  14. Petrovic,(2007) "Decision Support tool for multi-objective job shop scheduling problems with linguistically quantified decision function".
  15. N. Sujatha and K. Iyakutty ". Improved fuzzy c-mean clustering of web usage data with genetic algorithm "
  16. JAY VERKUILEN "Assigning Membership in a Fuzzy Set Analysis" University of Illinois, Urbana-Champaign
  17. Huang GuoJun and Hao ping," An Approach for Detecting Approximately Duplicate Data Warehouse Records"College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou 310032, China,2010 International Conference on Computer Application and System Modeling (ICCASM 2010)
  18. Teh Ying Wah, Ng Hooi Peng, and Ching Sue Hok "Building Data Warehouse "Department of Information Science,University Malaya Malaysia Proceedings of the 24th South East Asia Regional Computer Conference, November 18-19, 2007, Bangkok, Thailand.
Index Terms

Computer Science
Information Sciences


Data Mart Data repository ETL Fuzzy logic aggregation summarization and decision making