Data Virtualization Layer Key Role in Recent Analytical Data Architectures

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Abstract:

The amount of data, its heterogeneity and the speed at which it is generated are increasingly diverse and the current systems are not able to handle on-demand real-time data access. In traditional data integration approaches such as ETL, physically loading the data into data stores that use different technologies is becoming costly, time-consuming, inefficient, and a bottleneck. Recently, data virtualization has been used to accelerate the data integration process and provides a solution to previous challenges by delivering a unified, integrated, and holistic view of trusted data, on-demand and in real-time. This paper provides an overview of traditional data integration, in addition to its limits. We discuss data virtualization, its core capabilities and features, how it can complement other data integration approaches, and how it improves traditional data architecture paradigms.

Citation

Akermi, M., Hadj Taieb, M. A., Ben Aouicha, M. (2023). Data Virtualization Layer Key Role in Recent Analytical Data Architectures. In: Abraham, A., Pllana, S., Casalino, G., Ma, K., Bajaj, A. (eds) Intelligent Systems Design and Applications. ISDA 2022. Lecture Notes in Networks and Systems, vol 716. Springer, Cham. https://doi.org/10.1007/978-3-031-35501-1_42

@inproceedings{Akermi2023a,
  address={Cham},
  title={Data Virtualization Layer Key Role in Recent Analytical Data Architectures},
  DOI={10.1007/978-3-031-35501-1_42},
  booktitle={Intelligent Systems Design and Applications},
  publisher={Springer Nature Switzerland},
  author={Akermi, Montasser and Hadj Taieb, Mohamed Ali and Ben Aouicha, Mohamed},
  editor={Abraham, Ajith and Pllana, Sabri and Casalino, Gabriella and Ma, Kun and Bajaj, Anu},
  year={2023},
  pages={415–426}
}