Fatma Abdelhédi, Geneviève Pujolle, Olivier Teste, Gilles Zurfluh


With decision support systems, decision-makers analyse data in data marts extracted from production bases. The data-mart schema design is generally performed by expert designers (administrator or computer specialist). With data-driven, requirement-driven or hybrid-driven approaches, this designer builds a data-mart defining facts (analysis subjects) and analysis axes. This process, based on data sources and decision-makers requirements, often turns out to be approximate and complex. We propose to design a data-mart schema by the decision-maker himself, following a hybrid-driven approach. Using an assistance process that visualises successively intermediate schemas built from data sources, the decision-maker gradually builds his multidimensional schema. He determines measures to be analysed, dimensions hierarchies within dimensions. A CASE tool based on this concept has been developed.


  1. Annoni, E. et al., 2006. Towards Multidimensional Requirement Design. Data Warehousing and Knowledge Discovery, 75-84.
  2. Giorgini, P., Rizzi, S. & Garzetti, M., 2005. Goal-oriented requirement analysis for data warehouse design. Dans Proceedings of the 8th ACM international workshop on Data warehousing and OLAP. Bremen, Germany: ACM, p. 47-56.
  3. Golfarelli, M., Maio, D. & Rizzi, S., 1998. The Dimensional Fact Model: a conceptual model for data warehouses. Int. Journal of Cooperative Information Systems, 7(2&3), 215-247.
  4. Jerbi, H. et al., 2009. Applying recommendation technology in OLAP systems. Enterprise Information Systems, 220-233.
  5. Malinowski, E. & Zimányi, E., 2006. Hierarchies in a multidimensional model: From conceptual modeling to logical representation. Data & Knowledge Engineering, 59(2), 348-377.
  6. Malinowski, E. & Zimányi, E., 2008. Designing Conventional Data Warehouses. Advanced data warehouse design, 251 -- 313.
  7. Moody, D. L. & Kortink, M. A., 2000. From enterprise models to dimensional models: a methodology for data warehouse and data mart design. DMDW'00, Sweden, 5.
  8. Phipps, C. & Davis, K., 2002. Automating data warehouse conceptual schema design and evaluation. Proc. 4th DMDW, Toronto, Canada.
  9. Pinet, F. & Schneider, M., 2009. A Unified Object Constraint Model for Designing and Implementing Multidimensional Systems. Dans Journal on Data Semantics XIII. p. 37-71.
  10. Prat, N., Akoka, J. & Comyn-Wattiau, I., 2006. A UMLbased data warehouse design method. Decision Support Systems, 42(3), 1449-1473.
  11. Ravat, F. et al., 2007. Graphical querying of multidimensional databases. Dans Advances in Databases and Information Systems. p. 298-313.
  12. Romero, O. & Abelló, A., 2010. Automatic validation of requirements to support multidimensional design. Data & Knowledge Engineering.
  13. Song, I. et al., 2008. SAMSTAR: An Automatic Tool for Generating Star Schemas from an Entity-Relationship Diagram. Dans Conceptual Modeling - ER 2008. p. 522-523.
  14. Trujillo, J., Lujan-Mora, S. & Song, I. Y., 2003. Applying UML for designing multidimensional databases and OLAP applications. Advanced Topics in Database Research, 2, 13-36.

Paper Citation

in Harvard Style

Abdelhédi F., Pujolle G., Teste O. and Zurfluh G. (2011). COMPUTER-AIDED DATA-MART DESIGN . In Proceedings of the 13th International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-989-8425-53-9, pages 239-246. DOI: 10.5220/0003501902390246

in Bibtex Style

author={Fatma Abdelhédi and Geneviève Pujolle and Olivier Teste and Gilles Zurfluh},
booktitle={Proceedings of the 13th International Conference on Enterprise Information Systems - Volume 1: ICEIS,},

in EndNote Style

JO - Proceedings of the 13th International Conference on Enterprise Information Systems - Volume 1: ICEIS,
SN - 978-989-8425-53-9
AU - Abdelhédi F.
AU - Pujolle G.
AU - Teste O.
AU - Zurfluh G.
PY - 2011
SP - 239
EP - 246
DO - 10.5220/0003501902390246