Exploring the Integration of Business Process with Nosql Databases in the Context of BPM

  • Asma Hassani
  • Sonia Ayachi Ghannouchi
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 736)


Business process is defined as a set of interrelated tasks or activities which allows the fulfillment of one of the organization’s objectives. Modeling business process can be applied in several domains such as healthcare, business, education, etc. Modeling such process allows to facilitate and understand the functioning of corresponding systems. Steps in the process need input data and generate new output data. Business Process Management Systems (BPMS) play the role to model, configure and execute business processes. These latters are facing new challenges toward big data area. Data in business process originate from multiple sources with a variety of formats and are generated in a high speed and hence need in one hand, a storage infrastructure gathering all data types and forms. And on the other hand, analytics infrastructure that makes those data ready for analysis is needed. Therefore, regarding the flexibility and the dynamics of the execution of learning process, Not Only SQL (NoSQL) databases should be taken into consideration. So, the idea of combining business process and NoSQL databases becomes one merging and critical research area. In this paper, we propose the adoption of a Nosql database schema with MongoDB to model learning data in the context of MOOCs. Then, we explore the idea of integrating such database with the designed and configured massive learning process.


Business process SQL NoSQL MongoDB Learning process BPMS Data storage 


  1. 1.
    Van der Aalst, W.M., Ter Hofstede, A.H.: YAWL yet another workflow language. Inf. Syst. 30(4), 245–275 (2005)CrossRefGoogle Scholar
  2. 2.
    Vera-Baquero, A., Colomo-Palacios, R., Molloy, O.: Business process analytics using a big data approach. IT Prof. 15(6), 29–35 (2013)CrossRefGoogle Scholar
  3. 3.
    Chen, C.P., Zhang, C.Y.: Data-intensive applications, challenges, techniques and technologies: a survey on big data. Inf. Sci. 275, 314–347 (2014)CrossRefGoogle Scholar
  4. 4.
    Gao, X.: Towards the next generation intelligent BPM–in the era of big data. In: Business Process Management, pp. 4–9 (2013)Google Scholar
  5. 5.
    Assunção, M.D., Calheiros, R.N., Bianchi, S., Netto, M.A., Buyya, R.: Big data computing and clouds: trends and future directions. J. Parallel Distrib. Comput. 79, 3–15 (2015)CrossRefGoogle Scholar
  6. 6.
    Van der Aalst, W.M., Ter Hofstede, A.H., Weske, M.: Business process management: a survey. In: Business Process Management, vol. 3, pp. 1–12. Springer, Heidelberg (2003)Google Scholar
  7. 7.
    Netjes, M., Reijers, H., Van der Aalst, W.M.: Supporting the BPM life-cycle with FileNet. In: Proceedings of the Workshop on Exploring Modeling Methods for Systems Analysis and Design (EMMSAD), pp. 497–508. Namur University, Namur (2006)Google Scholar
  8. 8.
    Laney, D.: 3D data management: controlling data volume, velocity, and variety, Technical report (2001).
  9. 9.
    Beyer, M.A., Laney, D.: The Importance of ‘Big Data’: A Definition. Gartner, Stamford, CT (2012)Google Scholar
  10. 10.
    Bello-Orgaz, G., Jung, J.J., Camacho, D.: Social big data: recent achievements and new challenges. Inf. Fusion 28, 45–59 (2016)CrossRefGoogle Scholar
  11. 11.
    Sharma, V., Dave, M.: SQL and NoSQL databases. Int. J. Adv. Res. Comput. Sci. Softw. Eng. 2(8), 20–27 (2012)Google Scholar
  12. 12.
    Meyer, A., Smirnov, S., Weske, M.: Data in business processes. No. 50. Universitätsverlag Potsdam (2011)Google Scholar
  13. 13.
    Wang, S., Lv, C., Wen, L., Wang, J.: Managing massive business process models and instances with process space. In: BPM (Demos), p. 91 (2014)Google Scholar
  14. 14.
    Yoo, Y.S., Yu, J., Bang, H.C., Park, C.H.: A study on data analysis process management system in MapReduce using BPM. In: Proceedings of the 4th International Conference on Security-Enriched Urban Computing and Smart Grid (SUComS), pp. 7–12 (2013)Google Scholar
  15. 15.
    Hassani, A., Ghanouchi, S.A.: Modeling of a collaborative learning process in the context of MOOCs. In: International Conference on Systems of Collaboration (SysCo), pp. 1–6 (2016)Google Scholar
  16. 16.
    Kahloun, F., Ayachi, S.A.: Evaluating the quality of business process models based on measures and criteria in higher education developing a framework for continuous quality improvement. In: ISDA Conference (2016)Google Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Laboratory RIADI-GDLENSIMannoubaTunisia
  2. 2.High Institute on Management of SousseSousseTunisia

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