Empirical Validation of WebQMDW Model for Quality-based External Web Data Source Incorporation in a Data Warehouse

In recent years, World Wide Web has emerged as the most promising external data source for organizations’ Data Warehouses for valuable insights required in comprehensive decision making to gain a competitive edge. However, when the Data Warehouse uses external data sources from the Web without quality evaluation, it can adversely impact its quality. Quality models have been proposed in the research literature to evaluate and select Web Data sources for their integration in a Data Warehouse. However, these models are only conceptually proposed and not empirically validated. Therefore, in this paper, the authors present the empirical validation conducted on a set of 57 subjects to thoroughly validate the set of 22 quality factors and the initial structure of the multi-level, multi-dimensional WebQMDW quality model. The validated and restructured WebQMDW model thus obtained can significantly enhance the decision-making in the DW by selecting high-quality Web Data Sources.

@article{Bhutani2021,
  title     = {Empirical Validation of WebQMDW Model for Quality-based External Web Data Source Incorporation in a Data Warehouse},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {12},
  number    = {8},
  year      = {2021},
  publisher = {The Science and Information Organization},
  author    = {Priyanka Bhutani and Anju Saha and Anjana Gosain},
  doi       = {10.14569/IJACSA.2021.0120824},
  url       = {https://doi.org/10.14569/IJACSA.2021.0120824}
}