[defensesystems] Enabling battlefield big data ‘on the move’

From Defense Department commanders down to troops on the battlefield, the most challenging aspect of big data today is that it is “big.“ Data has swept into every military function and is now a critical component of most every mission, particularly in a restricted budget climate where the military must extract more valuable information with less manpower.

[siliconangle] The cloud + Big Data, a love fest : Analysis and forecasts

Kicking off the first day of Strata Conference in Santa Clara, California, the SiliconAngle CEO John Furrier and Wikibon CEO David Vellante, theCUBE regular co-hosts, talked with Jeff Kelly, Principal Research Contributor with Wikibon, discussing the new Wikibon’s2013 Big Data Vendor Review and Market Forecast report that was released yesterday.

[siliconangle] Big data infrastructure goes far beyond Hadoop #BigDataSV

Wikibon Principal Research Contributor Jeff Kelly provides an inclusive basic tutorial of the big data environment, including technologies, skill sets, and use cases, in “Big Data: Hadoop, Business Analytics and Beyond”, and while the environment starts with Hadoop and Map Reduce, it extends far beyond that. While parts of this report may seem basic to technical readers, it provides an excellent overview of technologies, pros and cons, and market issues such as the lack of trained technical personnel and data scientists.

[informationweek] 16 Top Big Data Analytics Platforms

Revolutionary. That pretty much describes the data analysis time in which we live. Businesses grapple with huge quantities and varieties of data on one hand, and ever-faster expectations for analysis on the other. The vendor community is responding by providing highly distributed architectures and new levels of memory and processing power. Upstarts also exploit the open-source licensing model, which is not new, but is increasingly accepted and even sought out by data-management professionals.

[forbes] Big Data Debates: Individuals Vs. Teams

Gregory Piatetsky recently ran a poll on his popular KDnuggets website where he asked his readers to vote for the preferred way to build data science capabilities in their organizations. The poll was prompted by the strong reaction to a post by Michael Mout in which he advised employers not to advertise for “data scientists” but rather to hire computer scientists, statisticians, and database administrators and combine them into a data science team.

[forbes] Top 10 Big Data Pure-Plays 2014

Wikibon published today the “Big Data Vendor Revenue and Market Forecast 2013-2017” report which lists more than 70 big data vendors with total 2013 revenues of $18.6 billion, growing at an annual rate of 58%. Here are the top ten big data vendors that derived 100% of their 2013 revenues from big data products and services, according to Wikibon’s estimates:

[forbes] Big Data: 5 Reasons Why Hadoop Is Ready for Enterprise Prime Time

As 2014 gets into full swing, Hadoop is increasingly being used for applications that are integral to daily business operations. No longer is Hadoop viewed by some organizations as just a platform for big data proof-of-concept applications. IT leaders should be developing a strategy for production-ready infrastructure, now, so they are ready to leverage the emerging technical advances that make Hadoop more capable of supporting business-critical big data applications.