{"id":{"repo_id":"aachen","oai_identifier":"oai:publications.rwth-aachen.de:59260"},"canonical_url":"https://search.dev.ndltd.org/etd/aachen/oai:publications.rwth-aachen.de:59260","repository":{"repo_id":"aachen","name":"RWTH Aachen University","base_url":"https://publications.rwth-aachen.de/oai2d"},"display":{"title":"Metadatenverwaltung zur qualitätsorientierten Informationslogistik in Data-Warehouse-Systemen","abstract":"The goal of a data warehouse system is to provide a comprehensive overview of the data available in a company, thereby supporting the management decisions. The integration of data coming from heterogeneous sources is one of the key problems in data warehousing. The technical foundations for the integration have been developed in recent years. However, an efficient technical infrastructure is not sufficient to address the following problems. Firstly, the data in the systems involved have different semantics. Secondly, there are different user requirements regarding the quality of data. Existing systems are unable to solve these problems. The present thesis supports the development of data warehouse systems paying special attention to the problems regarding semantics and data quality. The approach is based on the explicit modelling of meta data of data warehouse systems. In particular, the conceptual context, the quality requirements, and the quality characteristics of the individual system components are represented in a formal model. The main contributions of the present thesis are, firstly, an extended meta model of the architecture and processes of a data warehouse system and, secondly, a quality model for the systematic representation of quality requirements and measurements. Furthermore, a classification of quality dimensions and factors is developed that can be used for an extensive quality management in data warehouse systems. The meta data is applied in a model for quality management as well as in a methodology for quality-oriented data integration. The methodology developed in this work uses the meta data by combining different existing approaches to data integration. The results of the present work are validated in various case studies in industrial contexts and in international research projects.","abstract_html":"The goal of a data warehouse system is to provide a comprehensive overview of the data available in a company, thereby supporting the management decisions. The integration of data coming from heterogeneous sources is one of the key problems in data warehousing. The technical foundations for the integration have been developed in recent years. However, an efficient technical infrastructure is not sufficient to address the following problems. Firstly, the data in the systems involved have different semantics. Secondly, there are different user requirements regarding the quality of data. Existing systems are unable to solve these problems. The present thesis supports the development of data warehouse systems paying special attention to the problems regarding semantics and data quality. The approach is based on the explicit modelling of meta data of data warehouse systems. In particular, the conceptual context, the quality requirements, and the quality characteristics of the individual system components are represented in a formal model. The main contributions of the present thesis are, firstly, an extended meta model of the architecture and processes of a data warehouse system and, secondly, a quality model for the systematic representation of quality requirements and measurements. Furthermore, a classification of quality dimensions and factors is developed that can be used for an extensive quality management in data warehouse systems. The meta data is applied in a model for quality management as well as in a methodology for quality-oriented data integration. The methodology developed in this work uses the meta data by combining different existing approaches to data integration. 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The integration of data coming from heterogeneous sources is one of the key problems in data warehousing. The technical foundations for the integration have been developed in recent years. However, an efficient technical infrastructure is not sufficient to address the following problems. Firstly, the data in the systems involved have different semantics. Secondly, there are different user requirements regarding the quality of data. Existing systems are unable to solve these problems. The present thesis supports the development of data warehouse systems paying special attention to the problems regarding semantics and data quality. The approach is based on the explicit modelling of meta data of data warehouse systems. In particular, the conceptual context, the quality requirements, and the quality characteristics of the individual system components are represented in a formal model. The main contributions of the present thesis are, firstly, an extended meta model of the architecture and processes of a data warehouse system and, secondly, a quality model for the systematic representation of quality requirements and measurements. Furthermore, a classification of quality dimensions and factors is developed that can be used for an extensive quality management in data warehouse systems. The meta data is applied in a model for quality management as well as in a methodology for quality-oriented data integration. The methodology developed in this work uses the meta data by combining different existing approaches to data integration. The results of the present work are validated in various case studies in industrial contexts and in international research projects."]},{"key":"dc:source","label":"Dc Source","values":["Aachen : Publikationsserver der RWTH Aachen University XII, 271 S. : graph. Darst. (2003). doi:10.18154/RWTH-CONV-121063 = Aachen, Techn. 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