Analyzing and Improving Data Quality

Autores
Buccella, Agustina; Cechich, Alejandra; Domingo, Gonzalo
Año de publicación
2008
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Data quality is a research area strongly investigated during the 90’s. However, few companies in Argentina apply data quality methodologies or tools during the analysis, design or implementation phases of software development process. Developers generally use techniques to design systems such as UML without considering mechanisms for future data quality problems. In this work we propose a methodology in which the data quality is an essential part of the whole software development process. Early design decisions on data quality strongly impact on the system. Our methodology defines a set of practices to be applied on the software life cycle. In addition these practices act as a means to evaluate if systems already running fulfill with minimal data quality requirements.
Facultad de Informática
Materia
Ciencias Informáticas
data life cycle
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc/3.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/9624
Acceder
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oai_identifier_str oai:sedici.unlp.edu.ar:10915/9624
network_acronym_str SEDICI
repository_id_str 1329
network_name_str SEDICI (UNLP)
spelling Analyzing and Improving Data QualityBuccella, AgustinaCechich, AlejandraDomingo, GonzaloCiencias Informáticasdata life cycleData quality is a research area strongly investigated during the 90’s. However, few companies in Argentina apply data quality methodologies or tools during the analysis, design or implementation phases of software development process. Developers generally use techniques to design systems such as UML without considering mechanisms for future data quality problems. In this work we propose a methodology in which the data quality is an essential part of the whole software development process. Early design decisions on data quality strongly impact on the system. Our methodology defines a set of practices to be applied on the software life cycle. In addition these practices act as a means to evaluate if systems already running fulfill with minimal data quality requirements.Facultad de Informática2008-07info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArticulohttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdf57-63http://sedici.unlp.edu.ar/handle/10915/9624enginfo:eu-repo/semantics/altIdentifier/url/http://journal.info.unlp.edu.ar/wp-content/uploads/JCST-Jul08-1.pdfinfo:eu-repo/semantics/altIdentifier/issn/1666-6038info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc/3.0/Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2026-02-26T10:38:33Zoai:sedici.unlp.edu.ar:10915/9624Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292026-02-26 10:38:33.338SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Analyzing and Improving Data Quality
title Analyzing and Improving Data Quality
spellingShingle Analyzing and Improving Data Quality
Buccella, Agustina
Ciencias Informáticas
data life cycle
title_short Analyzing and Improving Data Quality
title_full Analyzing and Improving Data Quality
title_fullStr Analyzing and Improving Data Quality
title_full_unstemmed Analyzing and Improving Data Quality
title_sort Analyzing and Improving Data Quality
dc.creator.none.fl_str_mv Buccella, Agustina
Cechich, Alejandra
Domingo, Gonzalo
author Buccella, Agustina
author_facet Buccella, Agustina
Cechich, Alejandra
Domingo, Gonzalo
author_role author
author2 Cechich, Alejandra
Domingo, Gonzalo
author2_role author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
data life cycle
topic Ciencias Informáticas
data life cycle
dc.description.none.fl_txt_mv Data quality is a research area strongly investigated during the 90’s. However, few companies in Argentina apply data quality methodologies or tools during the analysis, design or implementation phases of software development process. Developers generally use techniques to design systems such as UML without considering mechanisms for future data quality problems. In this work we propose a methodology in which the data quality is an essential part of the whole software development process. Early design decisions on data quality strongly impact on the system. Our methodology defines a set of practices to be applied on the software life cycle. In addition these practices act as a means to evaluate if systems already running fulfill with minimal data quality requirements.
Facultad de Informática
description Data quality is a research area strongly investigated during the 90’s. However, few companies in Argentina apply data quality methodologies or tools during the analysis, design or implementation phases of software development process. Developers generally use techniques to design systems such as UML without considering mechanisms for future data quality problems. In this work we propose a methodology in which the data quality is an essential part of the whole software development process. Early design decisions on data quality strongly impact on the system. Our methodology defines a set of practices to be applied on the software life cycle. In addition these practices act as a means to evaluate if systems already running fulfill with minimal data quality requirements.
publishDate 2008
dc.date.none.fl_str_mv 2008-07
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Articulo
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/9624
url http://sedici.unlp.edu.ar/handle/10915/9624
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://journal.info.unlp.edu.ar/wp-content/uploads/JCST-Jul08-1.pdf
info:eu-repo/semantics/altIdentifier/issn/1666-6038
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc/3.0/
Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc/3.0/
Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0)
dc.format.none.fl_str_mv application/pdf
57-63
dc.source.none.fl_str_mv reponame:SEDICI (UNLP)
instname:Universidad Nacional de La Plata
instacron:UNLP
reponame_str SEDICI (UNLP)
collection SEDICI (UNLP)
instname_str Universidad Nacional de La Plata
instacron_str UNLP
institution UNLP
repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
repository.mail.fl_str_mv alira@sedici.unlp.edu.ar
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