Web: http://arxiv.org/abs/2209.10785

Sept. 23, 2022, 1:14 a.m. | Sasun Hambardzumyan, Abhinav Tuli, Levon Ghukasyan, Fariz Rahman, Hrant Topchyan, David Isayan, Mikayel Harutyunyan, Tatevik Hakobyan, Ivo Stranic, Da

cs.CV updates on arXiv.org arxiv.org

Traditional data lakes provide critical data infrastructure for analytical
workloads by enabling time travel, running SQL queries, ingesting data with
ACID transactions, and visualizing petabyte-scale datasets on cloud storage.
They allow organizations to break down data silos, unlock data-driven
decision-making, improve operational efficiency, and reduce costs. However, as
deep learning takes over common analytical workflows, traditional data lakes
become less useful for applications such as natural language processing (NLP),
audio processing, computer vision, and applications involving non-tabular
datasets. This paper …

arxiv deep learning lake lakehouse

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