Abstract
Companies that build data warehouses and use business intelligence for decision-making ultimately save money and increase profit. The warehousing technology proceeds a consolidation of data from a variety of sources that is designed to support strategic and tactical decision making. Data gathered from different sources have to flow in the target area to be analyzed. ETL process is responsible to perform this task. It pulls data out of the source systems and placing it into a data warehouse. However, Geographical Information Systems, pervasive systems and the positioning systems impose moving beyond the traditional warehousing management towards what is called Trajectory Data Warehousing. This later supports trajectory data. Therefore, traditional ETL processes are unable to perform their tasks when the mobility aspect is integrated. Towards this inadequacy, Trajectory ETL process emerges. Few are the works that dealt with. In this paper, we present a taxonomy of works that deeply investigate the ETL process modeling whatever the data kind that the warehousing chain supports, then we express how the trajectory ELT process based on the Model Driven Architecture approach aims at enhancing decision making.
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Azaiez, N., Akaichi, J.: What is the impact of mobility data integration on decision support systems’ modelling and evolution? Int. J. Inf. Syst. Serv. Sect. (IJISSS) 8(1), 1–12 (2016)
Boussaid, O., Bentayeb, F., Darmont, J.: An MAS-Based ETL approach for complex data. In: 10th ISPE International Conference on Concurrent Engineering: Research and Applications, Madeira, Portugal, pp. 49–52 (2003)
Leonardi, L.: A framework for trajectory data warehousing and visual OLAP analysis. Doctoral thesis Ca’foscari university of Venice (2014)
Schlesinger, L., Irmert, F., Lehner, W.: Supporting the ETL-process by web service technologies. Int. J. Web Grid Serv. (IJWGS) 1(1), 31–47 (2005)
Marketos, G., Frentzos, E., Ntoutsi, I., Pelekis, N., Raffaetà, A., Theodoridis, Y.: Building real-world trajectory warehouses. In: The International ACM Workshop on Data Engineering for Wireless and Mobile Access, Vancouver, BC, Canada, pp. 8–15 (2008)
Niinimäki, M., Niemi, T.: An ETL process for OLAP using RDF/OWL ontologies. In: Spaccapietra, S., Zimányi, E., Song, I.-Y. (eds.) Journal on Data Semantics XIII. LNCS, vol. 5530, pp. 97–119. Springer, Heidelberg (2009)
O.M.G.: Model Driven Architecture (MDA) (2004). http://www.omg.org/cgibin/doc?formal/03-06-01
Rifaieh, R., Benharkat, N.A.: Query-based data warehousing tool. In: 5th ACM International Workshop on Data Warehousing and OLAP, pp. 35–42 (2002)
Taktak, S., Alshomrani, S., Feki, J., Zurfluh, G.: An MDA approach for the evolution of data warehouses. IJDSST 7(3), 65–89 (2015)
Trujillo, J., Luján-Mora, S.: A UML based approach for modeling ETL processes in data warehouses. In: 22nd International Conference on Conceptual Modeling, Chicago, IL, USA, pp. 307–320 (2003)
Zekri, A., Akaichi, J.: An ETL for integrating trajectory data a medical delegate activities use case study. In: International Conference on Automation, Control, Engineering and Computer Science, pp. 138–147 (2015)
Rational Software Corporation: Using the Rose Extensibility Interface (REI). Technical report (2001)
Pelekis, N., Frentzos, E., Giatrakos, N., Theodoridis, Y.: HERMES: a trajectory DB engine for mobility-centric applications. Int. J. Knowl.-Based Organ. (IJKBO) 4(1), 19–41 (2014)
Azaiez, N., Akaichi, J.: How trajectory data modeling improves decision making? In: Proceedings of the 10th International Conference on Software Engineering and Applications, Colmar, Alsace, France, pp. 87–92 (2015)
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Azaiez, N., Akaichi, J. (2018). Integrating Trajectory Data in the Warehousing Chain: A New Way to Handle the Trajectory ELT Process. In: De Pietro, G., Gallo, L., Howlett, R., Jain, L. (eds) Intelligent Interactive Multimedia Systems and Services 2017. KES-IIMSS-18 2018. Smart Innovation, Systems and Technologies, vol 76. Springer, Cham. https://doi.org/10.1007/978-3-319-59480-4_35
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DOI: https://doi.org/10.1007/978-3-319-59480-4_35
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