Abstract
Today, the cloud offers a large array of possibilities for storage, with this flexibility comes also complexity. This complexity stems from the variety of storage mediums, such as, blob storage or NoSQL tables, and also from the different cost tiers within these systems. A strategic thinking to navigate this complex cloud storage landscape is important, not only for cost saving but also for prioritizing information, this prioritization has wider implications in other domains such as the Big Data realm, especially for governance and efficiency. In this paper we propose a strategy centered around probabilistic graphical model (PGM), this heuristic oriented management and organizational strategy allows more tractability and efficiency, we also illustrate this approach with a case study applied to the insurance field.
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Many cloud providers (such as Microsoft Azure ML), offer anomaly detection algorithms as part of their machine learning packages.
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Batrouni, M., Finch, S., Wilson, S., Bertaux, A., Nicolle, C. (2018). Intelligent Cloud Storage Management for Layered Tiers. In: Luo, Y. (eds) Cooperative Design, Visualization, and Engineering. CDVE 2018. Lecture Notes in Computer Science(), vol 11151. Springer, Cham. https://doi.org/10.1007/978-3-030-00560-3_5
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DOI: https://doi.org/10.1007/978-3-030-00560-3_5
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