Internal Data Imputation in Data Warehouse Dimensions

Missing data occur commonly in data warehouses and may generate data usefulness problems. Thus, it is essential to address missing data to carry out a better analysis. There exists data imputation methods for missing data in fact tables, but not for dimension tables. Hence, we propose in this paper a data imputation method for data warehouse dimensions that is based on existing data and takes both intra- and inter-dimension relationships into account.