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EE599-Lec26-Hwang-BigData2-Nov26-2013-Updated

EE599-Lec26-Hwang-BigData2-Nov26-2013-Updated - What is...

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1 Prof. Kai Hwang, USC, Nov. 22, 2013 Big-Data Analytics and Cloud Security for Trusted Cloud Computing Lec.26 of EE 599, Nov.26, 2013, Prof. Kai Hwang University of Southern California 1 boxshadowdwn Four Research Frontiers : BigData, Clouds, Social Networks, and the Internet of Things boxshadowdwn Shortage of Big-data Analytics, Security and Privacy hinder the acceptance of clouds, social networks and IoT services. boxshadowdwn Crucial R/D Challenges are identified and some new Approaches and Opportunities are revealed in this talk. 2 What is Data Science ? s) Data Science is the extraction of actionable knowledge directly from data through a process of discovery, hypothesis, and analytical hypothesis analysis. A Data Scientist is a practitioner who has sufficient knowledge of the overlapping regimes of expertise in business needs, domain knowledge, analytical skills and programming expertise to manage the end-to-end scientific method process through each stage in the big data lifecycle. Big Data refers to digital data volume, velocity and/or variety whose management requires scalability across coupled horizontal resources 3 Prof. Kai Hwang, USC, Nov. 25, 2013 Practitioners consider themselves Data Scientists Phones, Sensors, Social Networks and IoT are new sources of Big Data square4 Radar, Light Synchrotrons, Smartphones, Bio-imaging, RFID, Sensors, GPS, etc. 3 Hadoop and HDFS dominant Business – main emphasis at NIST – interested in analytics and assume HDFS Academia seem more interested in data management Clouds vs. Grids and Grid of Clouds Modern Big-Data Characteristics: 4 Prof. Kai Hwang, USC, Nov. 25, 2013 4 The Case of Photos (Images)
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5 Prof. Kai Hwang, USC, Nov. 25, 2013 1. Government Operation: National Archives and Records Administration, Census Bureau 2. Commercial: Finance in Cloud, Cloud Backup, Mendeley (Citations), Netflix, Web Search, Digital Materials, Cargo shipping 3. Defense: Sensors, Image surveillance, Situation Assessment 4. Healthcare and Life Sciences: Medical records, Graph and Probabilistic analysis, Pathology, Bioimaging, Genomics, Epidemiology, People Activity models, Biodiversity 5. Deep Learning and Social Media: Driving Car, Geolocate images/cameras, Twitter, Crowd Sourcing, Network Science, NIST benchmark datasets 51 Use Cases of Big Data: from TB’s to PB’s 5 6 Prof. Kai Hwang, USC, Nov. 25, 2013 6. The Ecosystem for Research : Metadata, Collaboration, Language Translation, Light source experiments 7. Astronomy and Physics: Sky Surveys, Large Hadron Collider at CERN and Belle Accelerator in Japan 8.
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