ASSESSING INFORMATION QUALITY FOR ON-LINE ANALYTICAL PROCESSING IN DATA WAREHOUSES
Information quality (IQ) is a critical factor in the success of the On-Line Analytical Processing (OLAP). Therefore, it is essential to measure the IQ in a data warehouse to ensure success in implementing OLAP. This paper presents a methodology to determine two IQ characteristics—accuracy and comprehensiveness—that are of critical importance to decision makers. 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. The model we present is simple and intuitive, and the algebra provides a means to concisely express complex OLAP queries.
Information Quality On-Line Analytical Processing(OLAP) Data Warehouse Data Cube
Su Ying Zhao Jing Jin Zhanming
Department of Business Strategy and Policy, Tsinghua University, Beijing, China School of Economics and Management Tsinghua University, Beijing, China
国际会议
北京
英文
2007-11-01（万方平台首次上网日期，不代表论文的发表时间）