Manuscript Number : IJSRSET1621111

A Study of a Detection and Elimination of Data Inconsistency in Data Integration

Authors(2) :-Dattatray R. Kale, Smita. Y. Aparadh

Data quality is highly important for running the effective business process. The real world data is spread over the various locations.A collections of these data from the different data sources and presenting the entire collection as a single source is difficult. Data integration involves combining data from numerous dissimilar sources, which are stored using different technologies and present a unified view of the data.Heterogenous and homogenous data is presented at various locations. A big problem in data integration is conflicts occurred into various data sources. Data Inconsistency exists when various and conflicting stories of the same data appear in different places. Data inconsistency shows unreliable information. So in this paper we are presenting the various techniques for finding data inconsistency in data integration.

Authors and Affiliations

Dattatray R. Kale
Department of Computer Engineering, Ashokrao Mane Polytechnic Vathar Tarf Vadgaon, Kolhapur, Maharashta, India
Smita. Y. Aparadh
Department of Computer Engineering, Ashokrao Mane Polytechnic Vathar Tarf Vadgaon, Kolhapur, Maharashta, India

Data Inconsistency, Data Integration, Data Source Quality.

  1. P.Anokhin, “Data Inconsistency detection and resolution in the integration of heterogeneous information sources”, Ph.D, Thesis, School of Information Technology and Engineering, George Mason University, 2001.
  2.  S. Agrawal, S. Deb, K. V. M. Naidu, and R. Rastogi, Efficient detection of distributed constraint violations, in ICDE, 2007.or and Second Author.
  3.  H. Galhardas, D. Florescu, D. Shasha, E. Simon, and C-A.Saita. Declarative Data Cleaning: Language, Model, and Algorithms. In International Conference on Very Large Data Bases, pages 371, 380, 2001.
  4. X.Chai Sayyadin, A. Doan, A.Rosenthal, and L.Seligman,”Analyzing and revising data integration schemas to improve their matchebility” in proceeding of 34th international Conference on very large Data base, 2008, PP, 773-784.
  5. A.Motro and P.Anokhin,”Fusionplex: Resolution of data inconsistency in the integration of heterogeneous data sources” Information Fusion, Vol.7, 2006, pp.176-196.
  6. M.A.H.Andez, S.J.Stolfo, and U.Fayyad,”Real-world data is dirty: Data Cleaning and the merge/purge problem” Data mining and knowledge Discovery, Vol2 1998 pp.9-37.
  7. Y.Papakonstontinou, S.Abiteboul and H.Garcia-Molina,”Object fusion mediator systems” in proceeding of 22nd international conference on very large database, 1996, pp.413-424.
  8. R.Y.Wang and D.M.strong,”Beyond accuracy: what data quality means to do consumers”, Journal of management Information systems, Vol.12, 1996, pp.5-30.
  9. J.M.Benitez, J.C.Martin and C.Roman,”Using fuzzy number for measuring quality of services in hotel industry”Tourisum management, Vol.28, 2007, pp.544-555.
  10. F.E.Uzoka “A fuzzy enhanced multicriteria decision analysis model for evaluating university academics research output”, Information knowledge systems management, Vol.7, 2008, pp.273-299.
  11. L.A. Zadeh,”The concept of linguistic variable and its application to approximate reasoning,” Information Science, Vol.8, 1975, pp.199-249.
  12. XIN WANG,LIN-PENG HUANG,XIAO-HUI XU,”A solution for Data Inconsistency in Data Integration”, Journal of Information Science and Engineering 27,681-695(2011).

Publication Details

Published in : Volume 2 | Issue 1 | January-February 2016
Date of Publication : 2016-03-05
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 532-535
Manuscript Number : IJSRSET1621111
Publisher : Technoscience Academy

Print ISSN : 2395-1990, Online ISSN : 2394-4099

Cite This Article :

Dattatray R. Kale, Smita. Y. Aparadh , " A Study of a Detection and Elimination of Data Inconsistency in Data Integration, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 2, Issue 1, pp.532-535, January-February-2016. Journal URL : https://res.ijsrset.com/IJSRSET1621111

Article Preview