Empirical validation of multidimensional model for data warehouse
Information is dormant somewhere inside the huge data; dataware house activates it and presents it in the form of required information to top level managers for decision making. Thus by the help of datawarehouse, we do not need to go through tomes of databases for analysis before making a decision....
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Published in | Proceedings of 3rd International Conference on Reliability, Infocom Technologies and Optimization pp. 1 - 6 |
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Main Authors | , , |
Format | Conference Proceeding |
Language | English |
Published |
IEEE
01.10.2014
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Subjects | |
Online Access | Get full text |
ISBN | 9781479968954 1479968951 |
DOI | 10.1109/ICRITO.2014.7014733 |
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Summary: | Information is dormant somewhere inside the huge data; dataware house activates it and presents it in the form of required information to top level managers for decision making. Thus by the help of datawarehouse, we do not need to go through tomes of databases for analysis before making a decision. There are some metrics proposed by researchers for multidimensional models for data warehouse. These metrics just provide the estimated or calculated measures and we need to empirically validate these at conceptual level. Two quality attributes effectiveness and understandability are used in this paper for estimating quality of these models. Here database management system software is used to obtain understandability in a pellucid way to attain more accuracy. We used a database management system as the unswayed or neutral subject. The execution time of each query is taken as the time taken by the subject to answer the question. Analysis is done using Pearson's correlation method and finally quality is predicted. |
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ISBN: | 9781479968954 1479968951 |
DOI: | 10.1109/ICRITO.2014.7014733 |