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Data quality management in a business intelligence environment : from the lens of metadata

Verbitskiy, Yuriy and Yeoh, William 2011, Data quality management in a business intelligence environment : from the lens of metadata, in ICIQ 2011 : Proceedings of 16th International Conference on Information Quality, University of South Australia, Adelaide, S. Aust..

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Title Data quality management in a business intelligence environment : from the lens of metadata
Author(s) Verbitskiy, Yuriy
Yeoh, William
Conference name International Conference on Information Quality (16th. 2011 : Adelaide, S. Aust.)
Conference location Adelaide, S. Aust.
Conference dates 18-19 Nov. 2011
Title of proceedings ICIQ 2011 : Proceedings of 16th International Conference on Information Quality
Editor(s) [unknown]
Publication date 2011
Conference series International Conference on Information Quality
Publisher University of South Australia
Place of publication Adelaide, S. Aust.
Keyword(s) data quality
metadata
business intelligence
Summary Business Intelligence is becoming more pervasive in many large and medium-sized organisations. Being a long term undertaking Business Intelligence raises many issues that an organisation has to deal with in order to improve its decision making processes. Data quality is one of the main issues exposed by Business Intelligence. Within the organisation data quality can affect attitudes to Business Intelligence itself, especially from the business users group. Comprehensive management of data quality is a crucial part of any Business Intelligence endeavour. It is important to address all types of data quality issues and come up with an all-in-one solution. We believe that extensive metadata infrastructure is the primary technical solution for management of data quality in Business Intelligence. Moreover, metadata has a more broad application for improving the Business Intelligence environment. Upon identifying the sources of data quality issues in Business Intelligence we propose a concept of data quality management by means of metadata framework and discuss the recommended solution.
Language eng
Field of Research 080699 Information Systems not elsewhere classified
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category E1 Full written paper - refereed
Copyright notice ©2011, University of South Australia
Persistent URL http://hdl.handle.net/10536/DRO/DU:30041748

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Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.