Gaining insight from large data volumes with ease
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 the context of the CMS experiment where Big Data tools are already playing or would play a significant role in daily operations
Availability note (English)
Available from https://www.epj-conferences.org/articles/epjconf/pdf/2019/19/epjconf_chep2018_04027.pdf; https://doaj.org/article/634d422de9904effac0c3150a487b272Additional details
Identifiers
Publishing Information
- Journal Title
- EPJ. Web of Conferences
- Journal Volume
- 214
- Journal Page Range
- vp.
- ISSN
- 2100-014X
Conference
- Title
- 23. International Conference on Computing in High Energy and Nuclear Physics
- Acronym
- CHEP 2018
- Dates
- 9-13 Jul 2018
- Place
- Sofia (Bulgaria)
INIS
- Country of Publication
- France
- Country of Input or Organization
- France
- INIS RN
- 53095681
- Subject category
- S97: MATHEMATICAL METHODS AND COMPUTING; S46: INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND TECHNOLOGY;
- Resource subtype / Literary indicator
- Conference
- Descriptors DEI
- CMS DETECTOR; MACHINE LEARNING; MONITORING; OPTIMIZATION
- Descriptors DEC
- ALGORITHMS; ARTIFICIAL INTELLIGENCE; LEARNING; MATHEMATICAL LOGIC; MEASURING INSTRUMENTS; RADIATION DETECTORS