A framework for data cleaning in data warehouses

Peng, Taoxin

Abstract

It is a persistent challenge to achieve a high quality of data in data warehouses. Data cleaning is a crucial task for such a challenge. To deal with this challenge, a set of methods and tools has been developed. However, there are still at least two questions needed to be answered: How to improve the efficiency while performing data cleaning? How to improve the degree of automation when performing data cleaning? This paper challenges these two questions by presenting a novel framework, which provides an approach to managing data cleaning in data warehouses by focusing on the use of data quality dimensions, and decoupling a cleaning process into several sub-processes. Initial test run of the processes in the framework demonstrates that the approach presented is efficient and scalable for data cleaning in data warehouses.

Citation

Peng, T. (2008). A framework for data cleaning in data warehouses. Enterprise Information Systems, 473-478

• Journal Article Type: Article
• Publication Date: 2008
• Deposit Date: Feb 8, 2010
• Publicly Available Date: May 16, 2017
• Print ISSN: 1751-7575
• Publisher: Taylor & Francis
• Peer Reviewed: Peer Reviewed
• Pages: 473-478
• Keywords: data cleaning; data warehouse; performance efficiency; automation; data quallity; decoupling; scalable
• Public URL: http://researchrepository.napier.ac.uk/id/eprint/3467