Implementing data cubes efficiently
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
Physical Database Design for Data Warehouses
ICDE '97 Proceedings of the Thirteenth International Conference on Data Engineering
Normal Forms for Multidimensional Databases
SSDBM '98 Proceedings of the 10th International Conference on Scientific and Statistical Database Management
Design and Analysis of Quality Information for Data Warehouses
ER '98 Proceedings of the 17th International Conference on Conceptual Modeling
Multidimensional normal forms for data warehouse design
Information Systems
Goal-Oriented Requirements Engineering: A Guided Tour
RE '01 Proceedings of the Fifth IEEE International Symposium on Requirements Engineering
Metrics for data warehouse conceptual models understandability
Information and Software Technology
An approach to engineering the requirements of data warehouses
Requirements Engineering
Agent oriented requirements engineering for a data warehouse
ACM SIGSOFT Software Engineering Notes
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Due to the increasing complexity of Data Warehouses (DW), continuous attention must be paid for evaluation of their quality throughout their design and development. DW quality depends on the quality of all requirements, conceptual, logical and physical models used for DW design. Various authors have proposed metrics to assure the quality of conceptual, logical and physical models for DW. However, there is no significant work in the DW literature to assure the quality of a requirements model. A good quality requirements model may lead to a good quality DW. In this paper, we propose a qualityoriented requirements model for a DW. In the proposed model, the notion of perspective is introduced to capture the intention of the agents (stakeholders) associated with their goals. The agent may view a soft goal from two perspectives: decisional and quality perspective. In the former, the agent may refine a soft goal into the goal having well defined criteria for its achievement and termed as decisional goal, whereas in the later the agent may define the various constraint (timing constraint, budgetary constraint etc.) associated with the decisional goals. The agents suggest the decisions for achieving their decisional goals considering these constraints. Thus, the decisional goals and the constraints specified in the decisional and quality perspective respectively should be maintained as meta-data of the DW. In this way, the quality of DW requirements model will be enhanced, which may lead to enhance the quality of conceptual, logical and physical model of DW.