An easily understood data warehouse model enables users to better identify and retrieve its data. It also makes it easier for users to suggest changes to its structure and content. Through an exploratory, empirical study, we compared the understandability of the star and traditional relational schemas. The results of our experiment contradict previous findings and show schema type did not lead to significant performance differences for a content identification task. Further, the relational schema actually led to slightly better results for a schema augmentation task. We discuss the implications of these findings for data warehouse design and future research.
This is an author-produced, peer-reviewed version of this article. © 2009, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (https://creativecommons.org/licenses/by-nc-nd/4.0/). The final, definitive version of this document can be found online at Decision Support Systems, doi: 10.1016/j.dss.2011.04.003
Schuff, David; Corral, Karen; and Turetken, Ozgur. (2011). "Comparing the Understandability of Alternative Data Warehouse Schemas: An Empirical Study". Decision Support Systems, 52(1), 9-20.