The approaches to data warehouse design are based on the assumption that source data are known in advance and available. While this assumption is true in common project situations, in some peculiar contexts it is not. This is the case of the French national project for analysis of energetic agricultural farms, that is the case study of this paper. Here, the above-mentioned methods can hardly be applied because source data can only be identified and collected once user requirements indicate a need. Besides, the users involved in this project found it very hard to express their analysis needs in abstract terms, i.e., without visualizing sample results of queries, which in turn would require availability of source data. To solve this deadlock we propose ProtOLAP, a tool-assisted fast prototyping methodology that enables quick and reliable test and validation of data warehouse schemata in situations where data supply is collected on users’ demand and users’ ICT skills are minimal. To this end, users manually feed sample realistic data into a prototype created by designers, then they access and explore these sample data using pivot tables to validate the prototype.