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Reviews of Big Data events from the editors of insideBIGDATA. Too see all the big data events in your area click on 'Event Calendar" listed in the drop down menu under "Resources"

Video: Why use Tables and Graphs for Knowledge Discovery System?

In this video from the 2016 HPC User Forum in Austin, John Feo from PNNL presents: Why use Tables and Graphs for Knowledge Discovery System? “GEMS software provides a scalable solution for graph queries over increasingly large data sets. As computing tools and expertise used in conducting scientific research continue to expand, so have the enormity and diversity of the data being collected. Developed at Pacific Northwest National Laboratory, the Graph Engine for Multithreaded Systems, or GEMS, is a multilayer software system for semantic graph databases. In their work, scientists from PNNL and NVIDIA Research examined how GEMS answered queries on science metadata and compared its scaling performance against generated benchmark data sets. They showed that GEMS could answer queries over science metadata in seconds and scaled well to larger quantities of data.”

Teradata Showcases Presto at 2016 Hadoop Summit

“Presto is a perfect fit with the Teradata Unified Data Architecture, an integrated analytical ecosystem for our enterprise customers. Presto enables companies to leverage standard ANSI SQL to execute interactive queries against Hadoop data. With Presto, utilizing Teradata’s Query Grid connector for Presto, customers can execute queries that originate in Teradata Integrated Data Warehouse that join data within the IDW and Hadoop leveraging Presto.”

Field Report: Deep Learning Summit 2016

insideBIGDATA was pleased to be on-hand for the recent Deep Learning Summit in Boston from May 12-13, 2016 as guests of the conference sponsor RE•WORK. Deep Learning (DL) researchers and industry leaders gathered for the event to hear extraordinary speakers, discovery emerging trends and expand their professional network, all around this hugely popular field.

Field Report: Qlik Qonnections 2016

Hot on the conference circuit this year, we here at insideBIGDATA were pleased to be Qlik’s guest for their Qlik Qonnections 2016 conference in Orlando, Florida on May 1-4. We had a blast at this annual tech extravaganza that’s hosted by one of the industry’s most innovative leaders.

Machine Learning Experts Gather in Boston

RE•WORK will host it’s annual East Coast events on Deep Learning and the Internet of Things in Boston on 12 & 13 May. Over 300 machine learning and IoT enthusiasts and experts will come together to hear keynote presentations, panel discussions, fireside chats and to explore the startup showcase area.

Open Data Science Conference East – Boston 2016

This year, ODSC is growing to bring together 2,500+ of the best and brightest at ODSC East in Boston! There will be 20+ workshops, 10+ training sessions, & 100+ speakers! Not to mention a career fair with top-notch companies ready to hire!

Video: Machine Learning Overview from NERSC

In this video from the HPC User Forum in Tucson, Prabhat from NERSC presents: Machine Learning. “Prabhat leads the Data and Analytics Services team at NERSC. His current research interests include scientific data management, parallel I/O, high performance computing and scientific visualization.”

Best Practices – Big Data Acceleration

“This talk will provide an overview of challenges in accelerating Hadoop, Spark and Memcached on modern HPC clusters. An overview of RDMA-based designs for multiple components of Hadoop (HDFS, MapReduce, RPC and HBase), Spark, and Memcached will be presented. Enhanced designs for these components to exploit in-memory technology and parallel file systems (such as Lustre) will be presented. Benefits of these designs on various cluster configurations using the publicly available RDMA-enabled packages from the OSU HiBD project ( will be shown.”

Video: Challenging Analytics Architectures from HP

Joseph George from HP presented this talk at the recent HPC User Forum. “This paper describes the HP Big Data Reference Architecture (BDRA) solution and outlines how a modern architectural approach to Hadoop provides the basis for consolidating multiple big data projects while, at the same time, enhancing price/performance, density, and agility. HP BDRA is a modern, flexible architecture for the deployment of big data solutions; it is designed to improve access to big data, rapidly deploy big data solutions, and provide the flexibility needed to optimize the infrastructure in response to the ever-changing requirements in a Hadoop ecosystem.”

Video: Barry Bolding from Cray Presents: HPC + D + A = HPDA?

“Pre-integrated with the Hadoop and Spark frameworks, the Urika-XA system combines the benefits of a turnkey analytics appliance with a flexible, open platform that you can modify for future analytics workloads. This single-platform consolidation of workloads reduces your analytics footprint and total cost of ownership.”