Abstract
The development of a data warehouse system is based on a conceptual multidimensional model, which provides a high level of abstraction in the accurate and expressive description of real-world situations. Once this model has been designed, the corresponding logical representation must be obtained as the basis of the implementation of the data warehouse according to one specific technology. However, there is a semantic gap between the dimension hierarchies modeled in a conceptual multidimensional model and its implementation. This gap particularly complicates a suitable treatment of summarizability issues, which may in turn lead to erroneous results from business intelligence tools. Therefore, it is crucial not only to capture adequate dimension hierarchies in the conceptual multidimensional model of the data warehouse, but also to correctly transform these multidimensional structures in a summarizability-compliant representation. A model-driven normalization process is therefore defined in this paper to address this summarizability-aware transformation of the dimension hierarchies in rich conceptual models.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Bodart, F., Patel, A., Sim, M., Weber, R.: Should optional properties be used in conceptual modelling? a theory and three empirical tests. Info. Sys. Research 12(4), 384–405 (2001)
Lechtenbörger, J., Vossen, G.: Multidimensional normal forms for data warehouse design. Inf. Syst. 28(5), 415–434 (2003)
Lehner, W., Albrecht, J., Wedekind, H.: Normal forms for multidimensional databases. In: Rafanelli, M., Jarke, M. (eds.) SSDBM, pp. 63–72. IEEE Computer Society, Los Alamitos (1998)
Lenz, H.J., Shoshani, A.: Summarizability in OLAP and statistical data bases. In: Ioannidis, Y.E., Hansen, D.M. (eds.) SSDBM, pp. 132–143. IEEE Computer Society, Los Alamitos (1997)
Luján-Mora, S., Trujillo, J., Song, I.Y.: A UML profile for multidimensional modeling in data warehouses. Data Knowl. Eng. 59(3), 725–769 (2006)
Malinowski, E., Zimányi, E.: Hierarchies in a multidimensional model: From conceptual modeling to logical representation. Data Knowl. Eng. 59(2), 348–377 (2006)
Malinowski, E., Zimányi, E.: Advanced data warehouse design: From conventional to spatial and temporal applications. Springer, Heidelberg (2008)
Mazón, J.N., Lechtenbörger, J., Trujillo, J.: Solving summarizability problems in fact-dimension relationships for multidimensional models. In: Song, I.Y., Abelló, A. (eds.) DOLAP, pp. 57–64. ACM, New York (2008)
Mazón, J.N., Lechtenbörger, J., Trujillo, J.: A survey on summarizability issues in multidimensional modeling. Data Knowl. Eng. 68(12), 1452–1469 (2009)
Pedersen, T.B., Jensen, C.S., Dyreson, C.E.: Extending practical pre-aggregation in on-line analytical processing. In: VLDB, pp. 663–674 (1999)
Pedersen, T.B., Jensen, C.S., Dyreson, C.E.: A foundation for capturing and querying complex multidimensional data. Inf. Syst. 26(5), 383–423 (2001)
Rafanelli, M., Shoshani, A.: STORM: A statistical object representation model. In: Michalewicz, Z. (ed.) SSDBM 1990. LNCS, vol. 420, pp. 14–29. Springer, Heidelberg (1990)
Rizzi, S., Abelló, A., Lechtenbörger, J., Trujillo, J.: Research in data warehouse modeling and design: dead or alive? In: Song, I.Y., Vassiliadis, P. (eds.) DOLAP, pp. 3–10. ACM, New York (2006)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Mazón, JN., Lechtenbörger, J., Trujillo, J. (2011). A Model-Driven Approach for Enforcing Summarizability in Multidimensional Modeling. In: De Troyer, O., Bauzer Medeiros, C., Billen, R., Hallot, P., Simitsis, A., Van Mingroot, H. (eds) Advances in Conceptual Modeling. Recent Developments and New Directions. ER 2011. Lecture Notes in Computer Science, vol 6999. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24574-9_10
Download citation
DOI: https://doi.org/10.1007/978-3-642-24574-9_10
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-24573-2
Online ISBN: 978-3-642-24574-9
eBook Packages: Computer ScienceComputer Science (R0)