PPT-A Synopses Data Engine for Interactive Extreme-Scale Analytics

Interactive ExtremeScale Analytics A SDE for Interactive ExtremeScale Analytics 1 Motivation using synopses for analytics at scale 2 A SDE for Interactive ExtremeScale Analytics Big . proc. ++ and TBON-FS. Michael Brim. What is Extreme Scale?. 100,000+ hosts. 1,000,000+ processes and threads. Deployed Systems. K Computer: ~88,000 8-core hosts . Tianhe-1A: ~7,000 12-core hosts + ~7000 accelerators. for the Internet of Things (IoT). Kevin Miller, Principal Program Manager, Azure IoT. BRK1552. Agenda. State of the art for . IoT. Architecture for building today. Patterns and anti-patterns. Demo. Architecture for the future. Abdul Saboor. BIG DATA ANALYTICS. Welcome To This Presentation. The Agenda for Presentation. Dryad. Nephele. MapReduce. Point # 1. Point # 2. Point # 5. Point # 3. Point # 4. Pregel. DEE. Point # 6. Judy Meyer. Principal Group Program Manager. DBI-B316. Breakout Sessions. CDP-B307. Azure Event Hub . (Fri 2:45). . Related content. Lab . . DBI-IL204. Speed Lab Azure Stream Analytics . . (Fri 8:30). Ethan . Kinory, Ph.D.. Ethan.Kinory@Rutgers.edu. Elearning. conference Rutgers-Camden. April 7, 2016. Office Mix. A free add-in for . Powerpoint. 2013+ (can be played back on any device).. Markup ordinary . Amanda McGowan. Seer Interactive. Overview. Overview of Digital Analytics. Purpose. Data Types. Social Analytics. Strategy & Setup. Interpreting the Data. Applying the Data. © 2015 Seer Interactive . Remco Chang. Assistant . Professor. Department of Computer Science. Tufts University. Big Data Visual Analytics:. A User-Centric Approach. “The . computer is incredibly fast, accurate, and stupid. Man is unbelievably slow, inaccurate, and brilliant. The marriage of the two is a force beyond calculation. is the use of:. data, . information technology, . statistical analysis, . quantitative methods, and . mathematical or computer-based models . to help managers gain improved insight about their business operations and . Dr. Brett M. Baker, AIG for Audit, NRC OIG. Manuel J. Mireles, Forensic Auditor, NGA OIG. Shiji S. Thomas, Forensic Accountant, NSF OIG. Analytics 101 Outline. At the end of this session you will be able to understand:. Date. Big Data is changing traditional data . warehousing. … data warehousing has reached the most significant tipping point since its inception. The biggest, possibly most elaborate data management system in IT is changing. . Different statistical distributions that are used to more accurately describe the extremes of a distribution. Normal distributions don’t give suitable information in the tails of the distribution. Extreme value analysis is primarily concerned with modeling the low probability, high impact events well. Data Science Reading Group Seminar. Thursday, May 18, 2017 . SAND2017-5377 PE. Proper Orthogonal Decomposition (POD) Closure Models for Turbulent Flows. Sandia National Laboratories is a . multi-mission . Challenges . and Opportunities. Remco. Chang. Tufts University. Visual Analytics = Human Computer. Visual analytics . is . “the . science of analytical reasoning facilitated by visual . interactive . Tufts. Remco. Chang. Assistant Professor. Tufts University. Problem Statement. The growth of data is exceeding our ability to analyze them. . The amount of digital information generated in the years 2002, 2006, 2010:.