Skip to main content
SpringerLink
Log in

A Data Warehouse Model for Business Processes Data Analytics

  • Conference paper
  • First Online:
Book cover Computational Science and Its Applications – ICCSA 2016 (ICCSA 2016)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9790))

Included in the following conference series:

Abstract

Business Process Management and Business Intelligence initiatives are commonly seen as separated organizational projects, suffering from lack of coordination, leading to a poor alignment between strategic management and operational business processes execution. Researchers and professionals of information systems have recognized that business processes are the key for identifying the user needs for developing the software that supports those needs. In this case, a process-driven approach could be used to obtain a Data Warehouse model for the Business Intelligence supporting software. This paper presents a process-based approach for identifying an analytical data model using as input a set of interrelated business processes, modeled with Business Process Model and Notation version 2.0, and the corresponding operational data model. The proposed approach ensures the identification of an analytical data model for a Data Warehouse repository, integrating dimensions, facts, relationships and measures, providing useful data analytics perspectives of the data under analysis.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. van der Aalst, W.M.: Business process management demystified: a tutorial on models, systems and standards for workflow management. In: Desel, J., Reisig, W., Rozenberg, G. (eds.) Lectures on Concurrency and Petri Nets, Advances in Petri Nets. LNCS, vol. 3098, pp. 1–65. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  2. Watson, H.J., Wixom, B.H.: The current state of business intelligence. IEEE Comput. 40(9), 96–99 (2007). doi:10.1109/MC.2007.331

    Article  Google Scholar 

  3. Melchert, F., Winter, R., Klesse, M.: Aligning process automation and business intelligence to support corporate performance management. In: Proceedings of the Tenth Americas Conference on Information Systems, pp 4053–4063 (2004)

    Google Scholar 

  4. Mili, H., Tremblay, G., Jaoude, G.B., Lefebvre, É., Elabed, L., Boussaidi, G.: Business process modeling languages: sorting through the alphabet soup. ACM Comput. Surv. 43(1) (2010). Doi:10.1145/1824795.1824799, http://doi.acm.org/10.1145/1824795.1824799

    Google Scholar 

  5. Sturm, A.: Enabling off-line business process analysis: a transformation based approach. In: BPMDS (2008)

    Google Scholar 

  6. Kaldeich, C., Oliveira e Sá, J.: Data warehouse methodology: a process driven approach. In: Persson, A., Stirna, J. (eds.) CAiSE 2004. LNCS, vol. 3084, pp. 536–549. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  7. Böehnlein, M., Ulbrich vom Ende A.: Business process oriented development of data warehouse structures. In: Proceedings of Data Warehousing, Physica Verlag (2000)

    Google Scholar 

  8. Dori, D., Feldman, R., Sturm, A.: Transforming an operational system model to a data warehouse model: a survey of techniques. In: Proceedings of the IEEE International Conference on Software – Science, Technology and Engineering (SwSTE), pp. 47–56 (2005)

    Google Scholar 

  9. OMG: Business process model and notation (BPMN), version 2.0. Technical report, Object Management Group (2011)

    Google Scholar 

  10. Cruz, E., Machado, R.J., Santos, M.Y.: Deriving a data model from a set of interrelated business process models. In: ICEIS 2015 - 17th International Conference on Enterprise Information Systems, vol. 1, pp 49–59 (2015)

    Google Scholar 

  11. Golfarelli, M., Rizzi, S., Vrdoljak, B.: Data warehouse design from XML sources. In: Proceedings of the 4th DOLAP (2001)

    Google Scholar 

  12. Hüsemann, B., Lechtenbörger, J., Vossen, G.: Conceptual data warehouse design. In: Proceedings of the 2nd DMDW, Stockholm, Sweeden (2000)

    Google Scholar 

  13. List, B., Schiefer, J., Tjoa, A.M., Quirchmayr, G.: Multidimensional business process analysis with the process warehouse. In: Abramowicz, W., Zurada, J. (eds.) Knowledge Discovery for Business Information Systems, pp. 211–227. Kluwer Academic Publishing, Dordrecht (2000)

    Google Scholar 

  14. Rizzi, S., Abelló, A., Lechtenbörger, J., Trujillo, J.: Research in data warehouse modeling and design: dead or alive? In: Proceedings of the 9th ACM International Workshop on Data Warehousing and OLAP (DOLAP 2006), pp. 3–10. ACM (2006)

    Google Scholar 

  15. Cruz, E., Machado, R.J., Santos, M.Y.: From business process modeling to data model: a systematic approach. In: 2012 Eighth International Conference on the Quality of Information and Communications Technology, pp. 205–210 (2012). doi:10.1109/QUATIC.2012.31

  16. Weske, M.: Business Process Management Concepts, Languages, Architectures. Springer, Heidelberg (2010)

    Google Scholar 

  17. Meyer, A.: Data in business process modeling. In: 5th Ph.D. Retreat of the HPI Research School on Service-oriented Systems Engineering (2010)

    Google Scholar 

Download references

Acknowledgments

This work has been supported by COMPETE: POCI-01-0145-FEDER-007043 and FCT (Fundação para a Ciência e Tecnologia) within the Project Scope: UID/CEC/00319/2013, and by Portugal Incentive System for Research and Technological Development, Project in co-promotion nº 002814/2015 (iFACTORY 2015-2018).

Author information

Authors and Affiliations

  1. ALGORITMI Research Centre, University of Minho, Guimarães, Portugal

    Maribel Yasmina Santos & Jorge Oliveira e Sá

Authors
  1. Maribel Yasmina Santos
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jorge Oliveira e Sá
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Maribel Yasmina Santos .

Editor information

Editors and Affiliations

  1. University of Perugia, Perugia, Italy

    Osvaldo Gervasi

  2. University of Basilicata, Potenza, Italy

    Beniamino Murgante

  3. Covenant University, Ota, Nigeria

    Sanjay Misra

  4. University of Minho, Braga, Portugal

    Ana Maria A.C. Rocha

  5. Polytechnic University, Bari, Italy

    Carmelo M. Torre

  6. Monash University, Clayton, Victoria, Australia

    David Taniar

  7. Kyushu Sangyo University, Fukuoka, Japan

    Bernady O. Apduhan

  8. Saint Petersburg State University, Saint Petersburg, Russia

    Elena Stankova

  9. Beijing University of Posts and Telecommunications, Beijing, China

    Shangguang Wang

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing Switzerland

About this paper

Cite this paper

Santos, M.Y., Oliveira e Sá, J. (2016). A Data Warehouse Model for Business Processes Data Analytics. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2016. ICCSA 2016. Lecture Notes in Computer Science(), vol 9790. Springer, Cham. https://doi.org/10.1007/978-3-319-42092-9_19

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-42092-9_19

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-42091-2

  • Online ISBN: 978-3-319-42092-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation