Discovering analytical preferences for personalizing what-if scenarios

Abstract

In this paper, we expose a hybridization methodology for helping to overcome the pitfalls of conventional What-If analysis process design and development by discovering the best recommendations for What-If analysis scenarios’ parameters using OLAP preferences. The hybridization process aims at assisting users during the decision-making processes by suggesting the most adequate scenario parameters according to their needs, making What-If scenarios more valuable, helping them during decision-making processes. The hybridization process provides several advantages to companies by making possible to study the behavior of a system without building it or creating the circumstances to make it happen in a business real-world system. Thus, knowing existing approaches for extracting preferences when dealing with OLAP application environments has clear business advantages. This work is about this, with a particular focus on discovering analytical preferences for personalizing What-If application scenarios.