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Big Ideas in Big Data? French-British Workshop on Big Data - London, November 2012 Monica Marinucci Director of Research, Oracle Global Education & Research Industry Unit

Copyright © 2011, Oracle and/or its affiliates. All rights reserved. The volume of earth-observation data from European Space Agency’s satellites passed 3PB in 2007 and the projection for 2020 is seven-fold The volume of worldwide climate data is expanding rapidly, creating challenges for both physical archiving and sharing, for ease of access of relevant information in a multidisciplinary environment Big Data in Research: Volume Exponential growth in data and the ability to access critical information Volume Very large quantities of data

Copyright © 2011, Oracle and/or its affiliates. All rights reserved. Velocity Extremely fast streams of data In high energy physics, the Large Hadron Collider generates 60TB of data per day The LOFAR Radio-Interferometre is producing 1.6TB/sec  setting new frontiers for radio-astronomy Big Data in Research: Velocity Rapid growth in speed of data generation © CERN

Copyright © 2011, Oracle and/or its affiliates. All rights reserved. Variety Wide range of data type characteristics The proposed Large Synoptic Survey Telescope will record 30 trillion bytes of image data every day In genomics on average scientists can fully sequence 167 individuals per week, generating 250GB of images or 200 movie files Big Data in Research: Variety Enterprise infrastructure ability to quickly accommodate new data sources © CERN

Copyright © 2011, Oracle and/or its affiliates. All rights reserved. Value High potential value if harnessed correctly In genomics the cost of sequencing is dropping by 50% every 5 months “… analysis, not sequencing, will be the main expense hurdle” ( Chris Ponting, University of Oxford, UK in Feb 2011 Article “Will Computers crash Genomics?”) Big Data in Research: Value Ability to translate raw data into information and knowledge

Copyright © 2011, Oracle and/or its affiliates. All rights reserved. New Frontiers in silico Materials Science: Nanotube composites Nature 447 The Carleton Wind Turbine (Extremely) Large Data Volumes Storage Metadata Access Exascale computing Global Collaborations Data sets integration Large scale simulations & modeling Context based Visualisation Cross-Discipline Research Cross-breeding of technology and innovative methods inspired by new collaborations and exchange of methods and approaches

Copyright © 2011, Oracle and/or its affiliates. All rights reserved. Oracle Labs To look for novel approaches and methodologies To focus on real-world outcomes: to develop technologies that will someday play a significant role in the evolution of technology and society. 4 main areas: Exploratory research Directed research Consulting Product incubation

Copyright © 2011, Oracle and/or its affiliates. All rights reserved. Erasmus Medical Centre Thanks to an Exadata-based solution, Erasmus Medical Centre achieved: For a 11 minute query, Exadata could improve it to 1 second, which is a major advantage for researchers to have immediate results Smart Scan and Flash Card : give performance in analyzing data. Hybrid Columnar Compression : gives performance in the ability to manipulate Tb of data (compression from 133 Gb to 11 Gb), with increased performance. Adding Oracle Database 11g features like partitioning gives more performance in manipulating, quantifying data obtained through the study of various genomes Complex data processing and analysis. Ability to load huge data information in minimum time store these data and their genomic DNA research results on storage disk have an efficient system able to give them query performance More information in the Press Release: Erasmus Medical Center employs Oracle Exadata for DNA researchErasmus Medical Center employs Oracle Exadata for DNA research

Copyright © 2011, Oracle and/or its affiliates. All rights reserved. PCA CLUSTERSHEATMAPCHEMICAL STRUCTURESCHROMOSOMES BRAIN ATLASPATIENT CORRELATIONPATHWAY NETWORKS DNA, RNA & PROTEIN SEQUENCING DATA Visualisation Ref: Allele1 Allele2 How is every record related to every other? What is the range and distribution of values? Courtesy of Prof. Peter van der Spek, Erasmus Medical Centre What is the underlying natural sequence variation? What are the supported regulatory relationships? How are the numeric attributes correlated? What are the major themes or concepts?

Copyright © 2011, Oracle and/or its affiliates. All rights reserved. Innovating with … © CERN

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