A Methodology for Information Quality Assessment in Data Warehousing

Author

Su, Ying ; Jin, Zhanming

Author_Institution

Resource Sharing & Promoting Center, Inst. of Sci. & Tech. Inf. of China, Beijing

fYear

2008

Firstpage

5521

Lastpage

5525

Abstract

This paper presents a methodology to determine two IQ characteristics-accuracy and comprehensiveness-that are of critical importance to data warehousing. This methodology can examine how the quality metrics of source information affect the quality for information outputs produced using the relational algebra operations selection, projection, and Cubic product. It can be used to determine how quality characteristics associated with diverse data sources affect the quality of the derived data. The study resulted in the development of a model of a data cube and an algebra to support IQ Assessment operations on this cube.

Keywords

data integrity; data mining; data models; data warehouses; relational algebra; relational databases; OLAP; data cube model development; data warehousing; information quality assessment methodology; information quality metric; relational algebra; Algebra; Communications Society; Companies; Data warehouses; Databases; Information analysis; Information management; Quality assessment; Quality management; Warehousing;

fLanguage

English

Publisher

ieee

Conference_Titel

Communications, 2008. ICC '08. IEEE International Conference on

Conference_Location

Beijing

Print_ISBN

978-1-4244-2075-9

Electronic_ISBN

978-1-4244-2075-9

Type

conf

DOI

10.1109/ICC.2008.1035

Filename

4534071