Context-based Data Quality Metrics in Data Warehouse Systems

The fact that Data Quality (DQ) depends on the context, in which data are produced, stored and used, is widely recognized in the research community. Data Warehouse Systems (DWS), whose main goal is to give support to decision making based on data, have had a huge growth in the last years, in researc...

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Main Authors: Flavia Serra, Adriana Marotta
Format: Article
Language:English
Published: Centro Latinoamericano de Estudios en Informática 2017-08-01
Series:CLEI Electronic Journal
Online Access:http://www.clei.org/cleiej-beta/index.php/cleiej/article/view/22
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author Flavia Serra
Adriana Marotta
author_facet Flavia Serra
Adriana Marotta
author_sort Flavia Serra
collection DOAJ
description The fact that Data Quality (DQ) depends on the context, in which data are produced, stored and used, is widely recognized in the research community. Data Warehouse Systems (DWS), whose main goal is to give support to decision making based on data, have had a huge growth in the last years, in research and industry. DQ in this kind of systems becomes essential. This work presents a proposal for identifying DQ problems in the domain of DWS, considering the different contexts that exist in each system component. This proposal may act as a first conceptual framework that guides the DQ-responsible in the management of DQ in DWS. The main contributions of this work are a thorough literature review about how contexts are used for evaluating DQ in DWS, and a proposal for assessing DQ in DWS through context-based DQ metrics.
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spelling doaj.art-a80e802fd5ed4e6abfa082ba5fe83b622022-12-22T02:01:53ZengCentro Latinoamericano de Estudios en InformáticaCLEI Electronic Journal0717-50002017-08-012023:13:2310.19153/cleiej.20.2.322Context-based Data Quality Metrics in Data Warehouse SystemsFlavia SerraAdriana MarottaThe fact that Data Quality (DQ) depends on the context, in which data are produced, stored and used, is widely recognized in the research community. Data Warehouse Systems (DWS), whose main goal is to give support to decision making based on data, have had a huge growth in the last years, in research and industry. DQ in this kind of systems becomes essential. This work presents a proposal for identifying DQ problems in the domain of DWS, considering the different contexts that exist in each system component. This proposal may act as a first conceptual framework that guides the DQ-responsible in the management of DQ in DWS. The main contributions of this work are a thorough literature review about how contexts are used for evaluating DQ in DWS, and a proposal for assessing DQ in DWS through context-based DQ metrics.http://www.clei.org/cleiej-beta/index.php/cleiej/article/view/22
spellingShingle Flavia Serra
Adriana Marotta
Context-based Data Quality Metrics in Data Warehouse Systems
CLEI Electronic Journal
title Context-based Data Quality Metrics in Data Warehouse Systems
title_full Context-based Data Quality Metrics in Data Warehouse Systems
title_fullStr Context-based Data Quality Metrics in Data Warehouse Systems
title_full_unstemmed Context-based Data Quality Metrics in Data Warehouse Systems
title_short Context-based Data Quality Metrics in Data Warehouse Systems
title_sort context based data quality metrics in data warehouse systems
url http://www.clei.org/cleiej-beta/index.php/cleiej/article/view/22
work_keys_str_mv AT flaviaserra contextbaseddataqualitymetricsindatawarehousesystems
AT adrianamarotta contextbaseddataqualitymetricsindatawarehousesystems