2022
DOI: 10.1016/j.procs.2022.12.083
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A Scalable framework for data lakes ingestion

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Cited by 7 publications
(3 citation statements)
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“…There are significant suggestions for data lake architecture, (13) as well as comparisons with data warehouses and publications that go through its concept, components, and problems. (14,15) From 2019, data lakes have increased their contributions to both the business and academic communities. However, the majority of data lake approaches are abstract, based on a particular use case or a specific layer of data lake architecture, and do not provide a comprehensive perspective from data extraction to information retrieval.…”
Section: Related Workmentioning
confidence: 99%
“…There are significant suggestions for data lake architecture, (13) as well as comparisons with data warehouses and publications that go through its concept, components, and problems. (14,15) From 2019, data lakes have increased their contributions to both the business and academic communities. However, the majority of data lake approaches are abstract, based on a particular use case or a specific layer of data lake architecture, and do not provide a comprehensive perspective from data extraction to information retrieval.…”
Section: Related Workmentioning
confidence: 99%
“…Furthermore, a review of all recently proposed metadata models in the literature is absolutely essential. Yet, metadata models serve as a broad framework for organizing metadata [24,25]. Thus, each metadata model is unique from other models in terms of the concepts it has presented, the functionalities it offers, or a variety of other variables.…”
Section: Metadata Modelsmentioning
confidence: 99%
“…Therefore, for a large-scale metadata system to perform well, distributed metadata management must be flexible and scalable [22]. In addition to that, according to [25], metadata management systems need a scalable feature as a relevant requirement to provide consistent storage scalability and performance. Furthermore, by adding data scalability to the eight relevant features identified in the paragraph above, it appears none of all the models reviewed support all of them.…”
Section: Ideal Requirements For a Generic And Extensible Metadata Modelmentioning
confidence: 99%