Advertisement

Requirements Engineering for Data Warehouses (RE4DW): From Strategic Goals to Multidimensional Model

  • Azadeh Nasiri
  • Waqas AhmedEmail author
  • Robert Wrembel
  • Esteban Zimányi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10651)

Abstract

Business Intelligence (BI) systems help organisations to monitor the fulfillment of business goals by means of tracking various Key Performance Indicators (KPIs). Data Warehouses (DWs) supply data to compute KPIs and therefore, are an important component of any BI system. While designing a DW to monitor KPIs, the following two important questions arise: (1) What data should be stored in a DW to measure a KPI, and (2) how the data should be modelled in a DW? We present a model-based Requirement Engineering (RE) framework to answer these questions. Our proposal consists of two major modelling components, namely, the context modelling component which is used to represent why and which data is required, and data modelling component which is used to model data as a multidimensional model.

Keywords

Data warehouse Requirements engineering Key performance indicators Multidimensional model 

References

  1. 1.
    Bonifati, A., Cattaneo, F.: Designing data marts for data warehouses. ACM Trans. Softw. Eng. Methodol. 10(4), 452–483 (2001)CrossRefGoogle Scholar
  2. 2.
    Chowdhary, P., Mihaila, G., Lei, H.: Model driven data warehousing for business performance management. In: Proceedings of the IEEE International Conference on e-Business, Engineering, pp. 483–487 (2006)Google Scholar
  3. 3.
    Frendi, M., Salinesi, C.: Requirements engineering for data warehousing. In Proceedings of Workshop on RE: Foundation for Software Quality, pp. 75–82 (2003)Google Scholar
  4. 4.
    Gallardo, J., Giacaman, G., Meneses, C., Marbán, Ó.: Framework for decisional business and requirements modeling in data mining projects. In: Corchado, E., Yin, H. (eds.) IDEAL 2009. LNCS, vol. 5788, pp. 268–275. Springer, Heidelberg (2009).  https://doi.org/10.1007/978-3-642-04394-9_33 CrossRefGoogle Scholar
  5. 5.
    Giorgini, C., Jazayeri, M., Mandrioli, D.: GRAnD: a goal-oriented approach to requirement analysis in data warehouses. Decis. Support Syst. 45(1), 4–21 (2008)CrossRefGoogle Scholar
  6. 6.
    Horkoff, J., Barone, D., Jiang, L., Yu, E., Amyot, D., Borgida, A., Mylopoulos, J.: Strategic business modeling: representation and reasoning. Softw. Syst. Model. 13(3), 1015–1041 (2014)CrossRefGoogle Scholar
  7. 7.
    Kimball, R.: The Data Warehouse Lifecycle Toolkit: Expert Methods for Designing, Developing, and Deploying Data Warehouses. Wiley, New York (1998)Google Scholar
  8. 8.
    Kimball, R., Ross, M.: The Data Warehouse Toolkit: The Complete Guide to Dimensional Modeling. Wiley, New York (2011)Google Scholar
  9. 9.
    Malinowski, E., Zimányi, E.: Requirements specification and conceptual modeling for spatial data warehouses. In: Meersman, R., Tari, Z., Herrero, P. (eds.) OTM 2006. LNCS, vol. 4278, pp. 1616–1625. Springer, Heidelberg (2006).  https://doi.org/10.1007/11915072_68 CrossRefGoogle Scholar
  10. 10.
    Maté, A., Trujillo, J., Mylopoulos, J.: Conceptualizing and specifying key performance indicators in business strategy models. In: Proceedings of the Conference on the Center for Advanced Studies on Collaborative Research, pp. 102–115. IBM Corp. (2012)Google Scholar
  11. 11.
    Mazón, J., Trujillo, J., Lechtenbörger, J.: Reconciling requirement-driven data warehouses with data sources via multidimensional normal forms. Data Knowl. Eng. 63(3), 725–751 (2007)CrossRefGoogle Scholar
  12. 12.
    Nasiri, A., Wrembel, R., Zimányi, E.: Model-based requirements engineering for data warehouses: From multidimensional modelling to KPI monitoring. In: Jeusfeld, M., Karlapalem, K. (eds.) Proceedings of International Workshop on Conceptual Modeling. LNCS, vol. 9382, pp. 198–209. Springer, Cham (2015).  https://doi.org/10.1007/978-3-319-25747-1_20 Google Scholar
  13. 13.
    Nasiri, A., Zimányi, E., Wrembel, R.: Requirements engineering for data warehouses. In: Proceedings of the Conference on Journes francophones sur les Entrepts de Donnes et l’Analyse en ligne, EDA, pp. 49–64 (2015)Google Scholar
  14. 14.
    Pardillo, J., Mazón, J., Trujillo, J.: Extending OCL for OLAP querying on conceptual MD models of DWs. Inf. Sci. 180(5), 584–601 (2010)CrossRefGoogle Scholar
  15. 15.
    Vaisman, I., Zimányi, E.: DW Systems: Design and Implementation. Springer, Heidelberg (2014)Google Scholar
  16. 16.
    Winter, R., Strauch, B.: Information requirements engineering for data warehouse systems. In: ACM Symposium on Applied, Computing, pp. 1359–1365 (2004)Google Scholar
  17. 17.
    Yu, E.: Towards modelling and reasoning support for early-phase requirements engineering. In: Proceedings of IEEE International Conference on Requirements Engineering, pp. 226–235 (1997)Google Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Azadeh Nasiri
    • 1
    • 2
  • Waqas Ahmed
    • 1
    • 2
    Email author
  • Robert Wrembel
    • 1
  • Esteban Zimányi
    • 2
  1. 1.Institute of Computing SciencePoznan University of TechnologyPoznańPoland
  2. 2.Department of Computer and Decision EngineeringUniversité Libre de BruxellesBrusselsBelgium

Personalised recommendations