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Guidelines of data quality issues for data integration in the context of the TPC-DI benchmark

Yang, Qishan, Ge, Mouzhi and Helfert, Markus orcid logoORCID: 0000-0001-6546-6408 (2017) Guidelines of data quality issues for data integration in the context of the TPC-DI benchmark. In: The International Conference on Enterprise Information System (ICEIS), 26-29 Apr, 2017, Porto, Portugal. ISBN 978-989-758-247-9

Nowadays, many business intelligence or master data management initiatives are based on regular data integration, since data integration intends to extract and combine a variety of data sources, it is thus considered as a prerequisite for data analytics and management. More recently, TPC-DI is proposed as an industry benchmark for data integration. It is designed to benchmark the data integration and serve as a standardisation to evaluate the ETL performance. There are a variety of data quality problems such as multi-meaning attributes and inconsistent data schemas in source data, which will not only cause problems for the data integration process but also affect further data mining or data analytics. This paper has summarised typical data quality problems in the data integration and adapted the traditional data quality dimensions to classify those data quality problems. We found that data completeness, timeliness and consistency are critical for data quality management in data integration, and data consistency should be further defined in the pragmatic level. In order to prevent typical data quality problems and proactively manage data quality in ETL, we proposed a set of practical guidelines for researchers and practitioners to conduct data quality management in data integration.
Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Uncontrolled Keywords:Data Quality; Data Integration; TPC-DI Benchmark; ETL
Subjects:Computer Science > Information technology
Computer Science > Information storage and retrieval systems
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Research Institutes and Centres > INSIGHT Centre for Data Analytics
Research Institutes and Centres > ADAPT
Published in: Hammoudi, Slimane, Smialek, Michal, Camp, Olivier and Filipe, Joaquim, (eds.) Proceedings of the 19th International Conference on Enterprise Information Systems - (Volume 1). Proceedings of the International Conference on Enterprise Information Systems 978-98(p.p. 1). SCITEPRESS. ISBN 978-989-758-247-9
Official URL:http://dx.doi.org/10.5220/0006334301350144
Copyright Information:© 2017 Scitepress
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
Funders:Science Foundation Ireland grant SFI/12/RC/2289, Insight- Centre for Data Analytics
ID Code:21814
Deposited On:24 May 2017 08:40 by Qishan Yang . Last Modified 13 Mar 2019 14:43

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