Prototyping Data Warehouse Systems
DaWaK '01 Proceedings of the Third International Conference on Data Warehousing and Knowledge Discovery
Environmental Modelling & Software
GRAnD: A goal-oriented approach to requirement analysis in data warehouses
Decision Support Systems
A method for the mapping of conceptual designs to logical blueprints for ETL processes
Decision Support Systems
An MDA approach for the development of data warehouses
Decision Support Systems
Automatic validation of requirements to support multidimensional design
Data & Knowledge Engineering
Modern software engineering methodologies meet data warehouse design: 4WD
DaWaK'11 Proceedings of the 13th international conference on Data warehousing and knowledge discovery
A model-driven framework for ETL process development
Proceedings of the ACM 14th international workshop on Data Warehousing and OLAP
Monitoring strategic goals in data warehouses with awareness requirements
Proceedings of the 27th Annual ACM Symposium on Applied Computing
Definition and analysis of new agricultural farm energetic indicators using spatial OLAP
ICCSA'12 Proceedings of the 12th international conference on Computational Science and Its Applications - Volume Part II
A case study on model-driven data warehouse development
DaWaK'12 Proceedings of the 14th international conference on Data Warehousing and Knowledge Discovery
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
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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.