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Kafka Summit San Francisco 2017

Streaming platforms at massive scale.

Aug 28, 2017 | San Francisco

Martin Marquez

Data Scientist & Data Streaming Services Project Leader, Cern

Manuel Martin Marquez obtained his first M.Sc. degree in Computer Sciences in 2008 and a second M.Sc. in Soft-computing and Intelligence Information Systems in 2011 both at the University of Granada, Spain. He is a member of the “Soft Computing and Intelligent Information Systems” (SCI2S) research group and the “Distributed Computational Intelligence and Time Series” research lab (DICITS). In 2007 he joined the Beam department of the European Centre for Nuclear Research (CERN). A that time he was co-leading the data management/engineering activities for the CERN Control Configuration Database and the Front-End Software Architecture, both projects of critical importance for improving the operations of the Large Hadrons Collider (LHC) and the rest of the CERN’s accelerators complex. Currently, Manuel is a CERN openlab Senior Research Fellow, in the CERN IT department. His main activities in this position focus on the development of new techniques and approaches for Big Data Analytics and the implementation of the CERN’s Data Analytics as a Service infrastructure – DAaaS. This Infrastructure centralizes and standardizes the complex data analytics requirements for the wide CERN research and engineering community. Manuel’s current areas of interest are time series analysis and modeling, distributed/parallel computational intelligence, data mining, and learning theory.

Sessions

Accelerating Particles to Explore the Mysteries of the Universe and How Kafka Can Help on That

Video & Slides

CERN uses the world’s largest and most complex scientific instruments to prove the fundamental structure of the universe. The organization is deploying a data streaming infrastructure, based on Kafka and IaaS cloud, to make its operations more scalable and efficient. This session expounds the motivations, selected architecture, challenging use cases ... Read More


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