Título:
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Frequent patterns in ETL workflows: An empirical approach
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Autor/a:
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Theodorou, Vasileios; Abelló Gamazo, Alberto; Thiele, Maik; Lehner, Wolfgang
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Otros autores:
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Universitat Politècnica de Catalunya. Departament d'Enginyeria de Serveis i Sistemes d'Informació; Universitat Politècnica de Catalunya. MPI - Modelització i Processament de la Informació; Universitat Politècnica de Catalunya. inSSIDE - integrated Software, Service, Information and Data Engineering |
Abstract:
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The complexity of Business Intelligence activities has driven the proposal of several approaches for the effective modeling of Extract-Transform-Load (ETL) processes, based on the conceptual abstraction of their operations. Apart from fostering automation and maintainability, such modeling also provides the building blocks to identify and represent frequently recurring patterns. Despite some existing work on classifying ETL components and functionality archetypes, the issue of systematically mining such patterns and their connection to quality attributes such as performance has not yet been addressed. In this work, we propose a methodology for the identification of ETL structural patterns. We logically model the ETL workflows using labeled graphs and employ graph algorithms to identify candidate patterns and to recognize them on different workflows. We showcase our approach through a use case that is applied on implemented ETL processes from the TPC-DI specification and we present mined ETL patterns. Decomposing ETL processes to identified patterns, our approach provides a stepping stone for the automatic translation of ETL logical models to their conceptual representation and to generate fine-grained cost models at the granularity level of patterns. |
Abstract:
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Peer Reviewed |
Materia(s):
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-Àrees temàtiques de la UPC::Informàtica::Sistemes d'informació -Knowledge representation (Information theory) -Expert systems (Computer science) -Empirical -ETL -Graph matching -Patterns -Representació del coneixement (Teoria de la informació) -Sistemes experts (Informàtica) |
Derechos:
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Attribution-NonCommercial-NoDerivs 3.0 Spain
http://creativecommons.org/licenses/by-nc-nd/3.0/es/ |
Tipo de documento:
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Artículo - Versión presentada Artículo |
Editor:
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Elsevier
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