학술논문

Validation of the data warehouse metrics using formal frameworks
Document Type
Conference
Source
2014 International Conference on Signal Propagation and Computer Technology (ICSPCT 2014) Signal Propagation and Computer Technology (ICSPCT), 2014 International Conference on. :239-243 Jul, 2014
Subject
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Engineering Profession
Fields, Waves and Electromagnetics
Signal Processing and Analysis
Couplings
Length measurement
Artificial intelligence
Size measurement
Complexity theory
Data warehouse
metrics
Briand's framework
Zuse's framework
formal validation
Language
Abstract
The DW consists of huge and complex set of data. Maintaining its quality is thus a matter of concern. The metrics are used to measure the quality factor of data warehouse. Several data model metrics of data warehouse have been proposed and validated in the literature to measure its quality attributes. There are two ways to validate the metrics. One is the formal validation and another is empirical validation. Our focus of study is on formal validation of metrics. Here in this paper, two formal frameworks have been surveyed for metrics validation namely; Briand's framework and Zuse's framework. Further, formal validation is illustrated with the help of Briand's framework and Zuse's framework by taking an example of each. Finally, both the formal frameworks have been compared and found easily understandable for validating the metrics formally.