Abstract
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.
Highlights
The importance of incorporating external data in the Data Warehouse to gain valuable insights into the market, competitors, products, or customers for comprehensive and unbiased decision making, has been long recognized in the research literature [1], [2]
In order to fill this research gap, in this paper, we present the empirical validation of the state-of-the-art multi-level, multidimensional WebQMDW (Web quality model for evaluating web sources for the DW) quality model [27] to enhance the decision making in a Data Warehouse
In this paper, we use the survey method as the validation method to thoroughly validate the set of quality factors and the structure of the WebQMDW model while following the guidelines and principles of research proposed by Kitchenham and Pfleeger [38]–[43]
Summary
The importance of incorporating external data in the Data Warehouse to gain valuable insights into the market, competitors, products, or customers for comprehensive and unbiased decision making, has been long recognized in the research literature [1], [2]. For the aforementioned task of quality-aware evaluation of Web Data Sources for a Data Warehouse, various quality models, frameworks, or a set of factors have been proposed in the research literature (see, for example, [19], [22]–[24],[4], [21], [20], [25], [26]). In order to fill this research gap, in this paper, we present the empirical validation of the state-of-the-art multi-level, multidimensional WebQMDW (Web quality model for evaluating web sources for the DW) quality model [27] to enhance the decision making in a Data Warehouse.
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