Abstract
The proliferation of multimedia data sources including text, images, videos, etc., driven by the extensive usage of social media and smart devices, highlights a significant need for real-time processing. This crucial issue becomes particularly evident in decision support systems, which enable organizations to make timely, informed choices. In this paper, we present a comprehensive systematic literature review (SLR) aimed at identifying relevant studies that address the problem of real-time Extract, Transform, Load (ETL) processes with complex and heterogeneous data sources, specifically focusing on multimedia data known as Big Data Multimedia. We aim to extract various methods and technologies to adapt typical ETL processes to handle multimedia data sources. Initially, a set of 5,882 papers was selected. After applying the different steps of the SLR, this selection was filtered down to 11 papers using specific selection criteria and a thorough analysis of each paper. The selected studies were then utilized to address the defined research questions. Finally, this paper discusses synthesized data, current research gaps, and provides recommendations for future work.
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Mallek, H., Ghozzi, F., Gargouri, F. (2024). Real-Time ETL for Multimedia Sources: A Systematic Literature Review. In: Abraham, A., Bajaj, A., Hanne, T., Siarry, P., Ma, K. (eds) Intelligent Systems Design and Applications. ISDA 2023. Lecture Notes in Networks and Systems, vol 1051. Springer, Cham. https://doi.org/10.1007/978-3-031-64850-2_6
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