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Gaining insight from large data volumes with ease

Efficient handling of large data-volumes becomes a necessity in today's world. It is driven by the desire to get more insight from the data and to gain a better understanding of user trends which can be transformed into economic incentives (profits, cost-reduction, various optimization of data...

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Detalles Bibliográficos
Autor principal: Kuznetsov, Valentin
Lenguaje:eng
Publicado: 2018
Materias:
Acceso en línea:http://cds.cern.ch/record/2647100
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author Kuznetsov, Valentin
author_facet Kuznetsov, Valentin
author_sort Kuznetsov, Valentin
collection CERN
description Efficient handling of large data-volumes becomes a necessity in today's world. It is driven by the desire to get more insight from the data and to gain a better understanding of user trends which can be transformed into economic incentives (profits, cost-reduction, various optimization of data workflows, and pipelines). In this paper, we discuss how modern technologies are transforming well established patterns in HEP communities. The new data insight can be achieved by embracing Big Data tools for a variety of use-cases, from analytics and monitoring to training Machine Learning models on a terabyte scale. We provide concrete examples within context of the CMS experiment where Big Data tools are already playing or would play a significant role in daily operations.
id cern-2647100
institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2018
record_format invenio
spelling cern-26471002019-09-30T06:29:59Zhttp://cds.cern.ch/record/2647100engKuznetsov, ValentinGaining insight from large data volumes with easeDetectors and Experimental TechniquesEfficient handling of large data-volumes becomes a necessity in today's world. It is driven by the desire to get more insight from the data and to gain a better understanding of user trends which can be transformed into economic incentives (profits, cost-reduction, various optimization of data workflows, and pipelines). In this paper, we discuss how modern technologies are transforming well established patterns in HEP communities. The new data insight can be achieved by embracing Big Data tools for a variety of use-cases, from analytics and monitoring to training Machine Learning models on a terabyte scale. We provide concrete examples within context of the CMS experiment where Big Data tools are already playing or would play a significant role in daily operations.CMS-CR-2018-209oai:cds.cern.ch:26471002018-09-18
spellingShingle Detectors and Experimental Techniques
Kuznetsov, Valentin
Gaining insight from large data volumes with ease
title Gaining insight from large data volumes with ease
title_full Gaining insight from large data volumes with ease
title_fullStr Gaining insight from large data volumes with ease
title_full_unstemmed Gaining insight from large data volumes with ease
title_short Gaining insight from large data volumes with ease
title_sort gaining insight from large data volumes with ease
topic Detectors and Experimental Techniques
url http://cds.cern.ch/record/2647100
work_keys_str_mv AT kuznetsovvalentin gaininginsightfromlargedatavolumeswithease