Efficient Incremental Computation of CUBE in Multiple Versions What-If Analysis
APWeb/WAIM '09 Proceedings of the Joint International Conferences on Advances in Data and Web Management
Incremental Computation for MEDIAN Cubes in What-If Analysis
APWeb/WAIM '09 Proceedings of the Joint International Conferences on Advances in Data and Web Management
The Tradeoff of Delta Table Merging and Re-writing Algorithms in What-If Analysis Application
APWeb/WAIM '09 Proceedings of the Joint International Conferences on Advances in Data and Web Management
An efficient method for maintaining data cubes incrementally
Information Sciences: an International Journal
What-if analysis in MOLAP environments
FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 2
A multidimensional data model with subcategories for flexibly capturing summarizability
Proceedings of the 25th International Conference on Scientific and Statistical Database Management
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In a data warehouse, real-world activities can trigger changes to dimensions and their hierarchical structure. E.g., organizations can be reorganized over time causing changes to reporting structure. Product pricing changes in select markets can result in changes to bundled options in those markets. Much of the previous work on trend analysis on data warehouses has mainly focused on efficient evaluation of complex aggregations (e.g., data cube) and data-driven hypothetical scenarios. In this paper, we consider hypothetical scenarios driven by changes to dimension hierarchies and introduce the notion of perspectives. Perspectives are parameters such as time or location that drive changes in other dimensions. We demonstrate how perspectives aid in capturing a whole suite of what-if analysis queries. We propose various semantics for OLAP queries under perspectives and develop techniques for the efficient evaluation of such queries. We have implemented our techniques on the Essbase OLAP engine which fundamentally supports changing dimensions, and conducted a comprehensive set of experiments. Our results demonstrate the feasibility, scalability, and utility of our techniques for evaluating what-if queries with perspectives.