Gargi Aggarwal

Work place: Information Technology Department, NSIT, New Delhi, India



Research Interests: Computational Science and Engineering, Computational Learning Theory, Computer Architecture and Organization, Data Structures and Algorithms


Gargi Aggarwal received her B.Tech degree in Computer Science from Indira Gandhi Delhi Technical University for Women (IGDTUW) in 2006. She received her M. Tech degree in Information Systems from University of Delhi in 2012. Ms. Aggarwal is a Teaching cum Research Fellow in the Division of IT at Netaji Subhas Institute of Technology, affiliated to University of Delhi. She is presently pursuing her PhD in Data Warehouse Quality from University of Delhi. Her research interests include Data Warehouse, Machine Learning and Software Quality Management.

Author Articles
Formal Validation of Data Warehouse Complexity Metrics using Distance Framework

By Gargi Aggarwal Sangeeta Sabharwal

DOI:, Pub. Date: 8 Oct. 2017

Data Warehouse is the cornerstone for organizations that base their strategic decisions on the large scale processing of numerical data. The success of the organization depends on these decisions and hence it becomes extremely important to have a quality data warehouse. Conceptual models have been widely recognized as a key determinant of data warehouse quality during the early stages of design. Recently, metrics have been proposed by authors based on hierarchies to quantify the complexity and inturn quality of the conceptual models of data warehouse. They have formally corroborated the measures against Briand’s property based framework to ensure their validity. However, Briand’s set of properties for software measures are a set of necessary but not sufficient measure axioms. They are advantageous to refute software metrics but not to validate them. Thus, we focus on the theoretical validation of the data warehouse conceptual model metrics using the Distance framework whose sufficiency is ensured by the measurement theory. The results indicate that the metrics are valid measures of the complexity of data warehouse conceptual models. Besides, validation by Distance framework assures that the metrics are in the ratio scale which further aids in data analysis.

[...] Read more.
Other Articles