This article originates in the efforts we made in the prototyping stage of a project conducted in the field of new agile BI applications. In this earlier work, we defined a model and algorithms for handling dynamic cubes that are updated as single fact comes in. The proposal includes the definition of a tree structure, called DyTree, used to store these cubes. A comprehensive experimental evaluation was conducted to observe the behavior of the proposal under some varying circumstances or settings, to help in understanding its working and to provide feedback to improve the solution. In this paper, we describe the workflow which has been used for this experimental evaluation. Performance metrics and behavioral metrics are defined as output of the experimental evaluation workflow. Different types of data sets and parameters for algorithms are the input used to configure the experiments. Using this environment and the prototype, some examples of experimental studies are presented. This shows how different scenarios can be simply constructed and how the experimental results can be used to understand the behavior of our proposal and to evaluate performance.