About: NIST Big Data Public Working Group   Sponge Permalink

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The NIST Big Data Public Working Group (NBD-PWG) was established on June 19, 2013. The scope of the NBD-PWG involves forming a community of interests from all sectors — including industry, academia, and government — with the goal of developing consensus on definitions, taxonomies, secure reference architectures, security and privacy, and — from these — a standards roadmap. Such a consensus would create a vendor-neutral, technology- and infrastructure-independent framework that would enable Big Data stakeholders to identify and use the best analytics tools for their processing and visualization requirements on the most suitable computing platform and cluster, while also allowing value-added from Big Data service providers.

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  • NIST Big Data Public Working Group
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  • The NIST Big Data Public Working Group (NBD-PWG) was established on June 19, 2013. The scope of the NBD-PWG involves forming a community of interests from all sectors — including industry, academia, and government — with the goal of developing consensus on definitions, taxonomies, secure reference architectures, security and privacy, and — from these — a standards roadmap. Such a consensus would create a vendor-neutral, technology- and infrastructure-independent framework that would enable Big Data stakeholders to identify and use the best analytics tools for their processing and visualization requirements on the most suitable computing platform and cluster, while also allowing value-added from Big Data service providers.
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  • The NIST Big Data Public Working Group (NBD-PWG) was established on June 19, 2013. The scope of the NBD-PWG involves forming a community of interests from all sectors — including industry, academia, and government — with the goal of developing consensus on definitions, taxonomies, secure reference architectures, security and privacy, and — from these — a standards roadmap. Such a consensus would create a vendor-neutral, technology- and infrastructure-independent framework that would enable Big Data stakeholders to identify and use the best analytics tools for their processing and visualization requirements on the most suitable computing platform and cluster, while also allowing value-added from Big Data service providers.
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