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Big Data and Open Science Data

This article is the fourth in an editorial series with a goal to provide a road map for scientific researchers wishing to capitalize on the rapid growth of big data technology for collecting, transforming, analyzing, and visualizing large scientific data sets.

Big Data Technology for Scientific Research

This article is the third in an editorial series with a goal to provide a road map for scientific researchers wishing to capitalize on the rapid growth of big data technology for collecting, transforming, analyzing, and visualizing large scientific data sets.

Primary Motivators of Big Data vis-à-vis Scientific Research

This article is the second in an editorial series with a goal to provide a road map for scientific researchers wishing to capitalize on the rapid growth of big data technology for collecting, transforming, analyzing, and visualizing large scientific data sets.

Brightspace Insights™ Empowers Instructors with Data From Across the Education Ecosystem

D2L (formerly “Desire2Learn”), a software leader that makes learning experiences better, unveiled the newest version of its Brightspace Insights analytics suite, marking a significant step forward in technology’s role in advancing learning globally. With this release, D2L is the first LMS provider to aggregate and capture streamed student data from across the entire learning ecosystem.

AstroCompute in the Cloud Grant Program Launches

The Square Kilometer Array (SKA) Organisation and AWS are launching the AstroCompute in the Cloud grant program to accelerate the development of innovative tools and techniques for processing, storing and analyzing the global astronomy community’s vast amounts of astronomic data in the cloud.

Big Data Capacity and Performance Supports Genome Analytics

When Stanislav Dusko Ehrlich – a world expert in microbiology and a pioneer of metagenomics – and his team set out to create their next generation biotech research platform, they needed a technology solution to support their stringent capacity and performance requirements for big data analytics.

DK Panda Presents: Big Data – Hadoop and Memcached

“As InfiniBand is getting used in scientific computing environments, there is a big demand to harness its benefits for enterprise environments for handling big data and analytics. This talk will focus on high-performance and scalable designs of Hadoop using native RDMA support of InfiniBand and RoCE. Designs for various components in Hadoop (such as HDFS, MapReduce, RPC, and HBASE) and their benefits based on the RDMA package for Apache Hadoop will be presented. RDMA-based design for scalable Memcached (used in Web 2.0) and the associated benefits will be presented.”

Interview: Splunk Brings Machine Data to Higher Education

“Splunk Enterprise is a platform for machine data. The technology delivers powerful and fast analytics to quickly unlock the value of machine data to IT and other users throughout an organization. In short, it’s a simple, effective way to collect, analyze and secure the massive streams of machine data generated by all IT systems and technology infrastructure.”

Intel’s Boyd Davis Talks Predictive Analytics and March Madness

“Intel’s goal is to encourage more innovative and creative uses for data as well as to demonstrate how big data and analytics technologies are impacting many facets of our daily lives, including sports. For example, coaches and their staffs are using real-time statistics to adjust games on-the-fly and throughout the season. From intelligent cameras to wearable sensors, a massive amount of data is being produced that, if analyzed in real-time, can provide a significant competitive advantage. Intel is among those making big data technologies more affordable, available, and easier to use for everything from helping develop new scientific discoveries and business models to even gaining the upper hand on good-natured predictions of sporting events.”

Interview: Active Archives for Managing and Storing Big Data

“Active archives are ideal for organizations that face exponential data growth or regularly manage high-volume unstructured data or digital assets. Target markets include life sciences, media and entertainment, education, research, government, financial services, oil and gas, and telecommunications, as well as general IT organizations requiring online data archive options.”