Skip to content

Research Paper On Star Schema Example

  • 1.

    Abdelhédi, F., Ravat, F., Teste, O., Zurfluh, G.: Selfstar: un système interactif pour la construction de schémas multidimensionnels. In: INFORSID, pp. 335–350 (2011)Google Scholar

  • 2.

    Abelló, A., Samos, J., Saltor, F.: Yam2: a multidimensional conceptual model extending UML. Inf. Syst. 31(6), 541–567 (2006)CrossRefGoogle Scholar

  • 3.

    Agirre, E., Alfonseca, E., Hall, K., Kravalova, J., Paşca, M., Soroa, A.: A study on similarity and relatedness using distributional and wordnet-based approaches. In: Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL’09), pp. 19–27. Association for Computational Linguistics, Stroudsburg (2009)Google Scholar

  • 4.

    Alhajj, R.: Extracting the extended entity-relationship model from a legacy relational database. Inf. Syst. 28(6), 597–618 (2003)CrossRefMATHGoogle Scholar

  • 5.

    Bargui, F., Ben-Abdallah, H., Feki, J.: A hybrid approach for data mart schema design from NL-OLAP requirements. In: Proceedings of the 14th International Conference on Applications of Natural Language to Information Systems (NLDB’09), pp. 295–296. Springer, Berlin (2010)Google Scholar

  • 6.

    Battaglia, A., Golfarelli, M., Rizzi, S.: Qbx: a case tool for data mart design. In: Troyer, O., Bauzer Medeiros, C., Billen, R., Hallot, P., Simitsis, A., Mingroot, H. (eds.) Advances in Conceptual Modeling. Recent Developments and New Directions. Lecture Notes in Computer Science, vol. 6999, pp. 358–363. Springer, Berlin (2011)Google Scholar

  • 7.

    Boulil, K., Pinet, F., Bimonte, S., Carluer, N., Lauvernet, C., Cheviron, B., Miralles, A., Chanet, J.P.: Guaranteeing the quality of multidimensional analysis in data warehouses of simulation results: application to pesticide transfer data produced by the macro model. Ecol. Inf. 16, 41–52 (2013)CrossRefGoogle Scholar

  • 8.

    Cabibbo, L., Torlone, R.: The design and development of a logical system for olap. Lect. Notes Comput. Sci. 1874, 1–10 (2000)CrossRefGoogle Scholar

  • 9.

    Carpani, F., Ruggia, R.: An integrity constraints language for a conceptual multidimensional data model. In: Proceedings of XIII International Conference on Software Engineering and Knowledge Engineering (SEKE), vol. 1 (2001)Google Scholar

  • 10.

    Feki, J., Hachaichi, Y.: Une démarche et un outil. J. Decis. Syst. 16(3), 303–333 (2007)CrossRefGoogle Scholar

  • 11.

    Franconi, E., Kamble, A.: The GMD data model for multidimensional information: a brief introduction. In: Data Warehousing and Knowledge Discovery, pp. 55–65. Springer, Berlin (2003)Google Scholar

  • 12.

    Ghozzi, F., Ravat, F., Teste, O., Zurfluh, G.: Contraintes pour modèle et langage multidimensionnels. Ingénierie des Systèmes d’Information 9(1), 9–34 (2004)CrossRefGoogle Scholar

  • 13.

    Golfarelli, M., Rizzi, S.: A methodological framework for data warehouse design. In: Proceedings of the 1st ACM International Workshop on Data Warehousing and OLAP, pp. 3–9. ACM, New York (1998)Google Scholar

  • 14.

    Golfarelli, M., Rizzi, S., Saltarelli, E.: Wand: a case tool for workload-based design of a data mart. In: 10th National Convention on Systems Evolution for Data Bases, pp. 422–426. Citeseer (2002)Google Scholar

  • 15.

    Gupta, R., Gosain, A.: Validating data warehouse quality metrics using PCA. In: ICDEM, pp. 170–172 (2010)Google Scholar

  • 16.

    Hachaichi, Y., Feki, J.: An automatic method for the design of multidimensional schemas from object oriented databases. Int. J. Inf. Technol. Decis. Mak. 12(06), 1223–1259 (2013)CrossRefMATHGoogle Scholar

  • 17.

    Hachaichi, Y., Feki, J., Ben-Abdallah, H.: Modélisation multidimensionnelle de documents xml centrés-données. J. Decis. Syst. 19(3), 313–345 (2010)CrossRef

  • Extraction–transformation–loading (ETL) tools are pieces of software responsible for the extraction of data from several sources, its cleansing, customization, reformatting, integration, and insertion into a data warehouse. Building the ETL process is potentially one of the biggest tasks of building a warehouse; it is complex, time consuming, and consumes most of data warehouse project’s implementation efforts, costs, and resources. Building a data warehouse requires focusing closely on understanding three main areas: the source area, the destination area, and the mapping area (ETL processes). The source area has standard models such as entity relationship diagram, and the destination area has standard models such as star schema, but the mapping area has not a standard model till now. In spite of the importance of ETL processes, little research has been done in this area due to its complexity. There is a clear lack of a standard model that can be used to represent the ETL scenarios. In this paper we will try to navigate through the efforts done to conceptualize the ETL processes. Research in the field of modeling ETL processes can be categorized into three main approaches: Modeling based on mapping expressions and guidelines, modeling based on conceptual constructs, and modeling based on UML environment. These projects try to represent the main mapping activities at the conceptual level. Due to the variation and differences between the proposed solutions for the conceptual design of ETL processes and due to their limitations, this paper also will propose a model for conceptual design of ETL processes. The proposed model is built upon the enhancement of the models in the previous models to support some missing mapping features.