Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/54391

TitleA process mining approach for discovering ETL black points
Author(s)Belo, Orlando
Dias, Nuno
Ferreira, Carlos
Pinto, Filipe
KeywordsData warehousing systems
ETL processes
Process mining
ETL efficiency and optimization
ETL black points
Issue date2017
PublisherSpringer-Verlag Berlin
JournalAdvances in Intelligent Systems and Computing
Abstract(s)ETL tasks are quite complex often leading to a very complex network of working processes. Many difficulties of their development come from the number of sources of information we need to work, the heterogeneity and dispersion of data, and from the complexity of the tasks to implement, in order to populate appropriately a data warehouse. Thus, it is not difficult to occur some undesirable situations related to ETL system design errors or to the implementation of faulty or inefficient tasks. Many of these situations are only detectable at run time. In this paper, we discuss in particular the case of ETL bottleneck situations - ETL black points -, which can occur during the execution of an ETL system, identifying them and characterizing them using process mining. Based on the process mining results analysis, it is possible to develop alternative implementations for inefficient tasks and improve the overall system performance.
TypeConference paper
URIhttp://hdl.handle.net/1822/54391
ISBN9783319565378
DOI10.1007/978-3-319-56538-5_43
ISSN2194-5357
Peer-Reviewedyes
AccessRestricted access (UMinho)
Appears in Collections:CAlg - Artigos em livros de atas/Papers in proceedings

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