Introduction to the special issue on data quality
Abstract
Poor data quality in databases, data warehouses, and information systems affects every application domain. Many data processing tasks, such as information integration, data sharing, information retrieval, information extraction, and knowledge discovery require various forms of data preparation and consolidation with complex data processing techniques. These tasks usually assume that the data input contains no missing, inconsistent or incorrect values. This leaves a large gap between the available “dirty” data and the machinery to effectively process the data for the application purposes. In addition, tasks such as data integration and information extraction may themselves introduce errors in the data.
Keywords
data quality, data warehouses, information systems, information integration, information extraction, data preparation
Date of this Version
9-2013
DOI
10.1016/j.is.2013.03.001
Comments
Information Systems (Journal), vol. 38, issue 6, pp 885-886