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dc.contributor.authorMuñoz, Lilia
dc.contributor.authorMazón, Jose Norberto
dc.contributor.authorTrujillo, Juan
dc.date.accessioned2018-06-13T20:24:48Z
dc.date.available2018-06-13T20:24:48Z
dc.date.issued11/01/2010
dc.identifier.urihttp://ridda2.utp.ac.pa/handle/123456789/4917
dc.descriptionIn data warehousing, Extract, Transform, and Load (ETL) processes are in charge of extracting the data from the data sources that will be contained in the data warehouse. Their design and maintenance is thus a cornerstone in any data warehouse development project. Due to their relevance, the quality of these processes should be formally assessed early in the development in order to avoid populating the data warehouse with incorrect data. To this end, this paper presents a set of measures with which to evaluate the structural complexity of ETL process models at the conceptual level. This study is, moreover, accompanied by the application of formal frameworks and a family of experiments whose aim is to theoretical and empirically validate the proposed measures, respectively. Our experiments show that the use of these measures can aid designers to predict the effort associated with the maintenance tasks of ETL processes and to make ETL process models more usable. Our work is based on Unified Modeling Language (UML) activity diagrams for modeling ETL processes, and on the Framework for the Modeling and Evaluation of Software Processes (FMESP) framework for the definition and validation of the measures.en_US
dc.description.abstractIn data warehousing, Extract, Transform, and Load (ETL) processes are in charge of extracting the data from the data sources that will be contained in the data warehouse. Their design and maintenance is thus a cornerstone in any data warehouse development project. Due to their relevance, the quality of these processes should be formally assessed early in the development in order to avoid populating the data warehouse with incorrect data. To this end, this paper presents a set of measures with which to evaluate the structural complexity of ETL process models at the conceptual level. This study is, moreover, accompanied by the application of formal frameworks and a family of experiments whose aim is to theoretical and empirically validate the proposed measures, respectively. Our experiments show that the use of these measures can aid designers to predict the effort associated with the maintenance tasks of ETL processes and to make ETL process models more usable. Our work is based on Unified Modeling Language (UML) activity diagrams for modeling ETL processes, and on the Framework for the Modeling and Evaluation of Software Processes (FMESP) framework for the definition and validation of the measures.en_US
dc.formatapplication/pdf
dc.language.isoengen_US
dc.rightshttps://creativecommons.org/licenses/by-nc-sa/4.0/
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectETL processesen_US
dc.subjectMeasure validationen_US
dc.subjectActivity diagramsen_US
dc.subjectengineeringData warehouse conceptual modelingQualityen_US
dc.subjectEmpirical Software engineeringen_US
dc.subjectData warehouse conceptual modelingen_US
dc.subjectQualityen_US
dc.titleA family of experiments to validate measures for UML activity diagrams of ETL processes in data warehousesen_US
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/publishedVersion


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