An empirical experimentation towards predicting understandability of conceptual schemas using quality metric
by Naveen Dahiya; Vishal Bhatnagar; Manjeet Singh
International Journal of Big Data Intelligence (IJBDI), Vol. 2, No. 1, 2015

Abstract: Data warehouse are used in organisations for efficient information delivery. The quality of a data warehouse is governed by the quality of conceptual, logical and physical data models. Conceptual model forms the base for design of logical/physical models. The conceptual model quality is assessed using quality metrics. The metrics for assessing the quality of conceptual schemas are based on size/structural complexity of schemas. Various statistical techniques show the existence of significant relationship between quality metrics and understanding time of conceptual models. In this paper, the authors analyse the ability of quality metrics in predicting the understandability of conceptual schemas using experimental empirical approach. Various statistical techniques are used for study and analysis. The results of empirical analysis show that few of the metrics are strong indicators for predicting the understandability of conceptual multidimensional models.

Online publication date: Tue, 17-Feb-2015

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Big Data Intelligence (IJBDI):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?


Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com