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Author Mezzanzanica, Mario ♦ Boselli, Roberto ♦ Cesarini, Mirko ♦ Mercorio, Fabio
Source ACM Digital Library
Content type Text
Publisher Association for Computing Machinery (ACM)
File Format PDF
Copyright Year ©2015
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Data quality ♦ ETL ♦ Data believability ♦ Data consistency ♦ Data verification
Abstract The data extracted from electronic archives is a valuable asset; however, the issue of the (poor) data quality should be addressed before performing data analysis and decision-making activities. Poor data quality is frequently cleansed using business rules derived from domain knowledge. Unfortunately, the process of designing and implementing cleansing activities based on business rules requires a relevant effort. In this article, we illustrate a model-based approach useful to perform inconsistency identification and corrective interventions, thus simplifying the process of developing cleansing activities. The article shows how the cleansing activities required to perform a sensitivity analysis can be easily developed using the proposed model-based approach. The sensitivity analysis provides insights on how the cleansing activities can affect the results of indicators computation. The approach has been successfully used on a database describing the working histories of an Italian area population. A model formalizing how data should evolve over time (i.e., a data consistency model) in such domain was created (by means of formal methods) and used to perform the cleansing and sensitivity analysis activities.
ISSN 19361955
Age Range 18 to 22 years ♦ above 22 year
Educational Use Research
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2015-03-02
Publisher Place New York
e-ISSN 19361963
Journal Journal of Data and Information Quality (JDIQ)
Volume Number 5
Issue Number 4
Page Count 28
Starting Page 1
Ending Page 28


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Source: ACM Digital Library