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big data

Sponsor Blog: Big Data Analytics a Better Bet to Battling Cyber Attacks

November 17, 2014
By Jay Aceto

Many information technology organizations are taking a different approach to cybersecurity that radically reduces the time to detect and respond to attempted cyber attacks.

Big Data Tools Cut Through the Fog of War

April 1, 2014
By Henry S. Kenyon

The U.S. Air Force is using big data analysis tools to create a picture of a battlefield or area of interest that can be monitored in real time as well as stored and replayed. By merging sensor streams with data tagging and trend detection software, this capability will allow analysts and warfighters to observe, track and potentially predict enemy force operations based on their observed behavior.

Trillions of Sensors Feed Big Data

February 1, 2014
By Michael A. Robinson

The emergence of big data combined with the revolution in sensor technology is having a synergistic effect that promises a boom in both realms. The ability to fuse sensor data is spurring the growth of large databases that amass more information than previously envisioned. Similarly, the growth of big data capabilities is spawning new sensor technologies and applications that will feed databases’ ever-increasing and diverse types of information.

Big Data Is Driving Information
Technology Planning and Investment

February 1, 2014
By Kent R. Schneider

This rarely happens, but for 2014, defense and technology analysts are in agreement that big data and cybersecurity are the two drivers in planning and investment for information technology, both in government and in industry. Most everything else will be enabling these two key capabilities. While much attention has been focused on the threats and work being done globally on cybersecurity, I want to focus on big data.

Big data is critical because, unless it is collected, analyzed, managed and made ubiquitously available, many analysts and decision makers will be buried in information they cannot use effectively in a timely fashion. It also is the starting and ending point for many of the technologies and capabilities we care about: networks, data centers, cloud initiatives, storage, search, analytics and secure access

Novel Big Data Reveals Global Human Behavior

February 1, 2014
By Rita Boland

The increasing presence of news sources on the Internet offers an unprecedented opportunity to access open-source intelligence for a variety of purposes. Researchers from several U.S. universities have collaborated to take advantage of these resources, creating a big data collection and distribution process applicable to disciplines ranging from social research to national security.

VIDEO: Should the Intelligence Community Embrace Big Data?

November 7, 2013
By Robert K. Ackerman

Big Data increasingly is viewed as the future of knowledge management, aided and abetted by the cloud. And, it would seem to be a perfect fit in the field of intelligence. But two longtime experts in intelligence take opposing views on the utility of big data for intelligence.

A Longtime Tool of the Community

October 1, 2013
By Lewis Shepherd

What do modern intelligence agencies run on? They are internal combustion engines burning pipelines of data, and the more fuel they burn the better their mileage. Analysts and decision makers are the drivers of these vast engines; but to keep them from hoofing it, we need big data.
 
The intelligence community necessarily has been a pioneer in big data since inception, as both were conceived during the decade after World War II. The intelligence community and big data science always have been intertwined because of their shared goal: producing and refining information describing the world around us, for important and utilitarian purposes.

Let’s stipulate that today’s big-data mantra is overhyped. Too many technology vendors are busily rebranding storage or analytics as “big data systems” under the gun from their marketing departments. That caricature rightly is derided by both information technology cognoscenti and non-techie analysts.

I personally understand the disdain for machines, as I had the archetypal humanities background and was once a leather-elbow-patched tweed-jacketed Kremlinologist, reading newspapers and human intelligence (HUMINT) for my data. I stared into space a lot, pondering the Chernenko-Gorbachev transition. Yet as Silicon Valley’s information revolution transformed modern business, media, and social behavior across the globe, I learned to keep up—and so has the intelligence community.

Twitter may be new, but the intelligence community is no Johnny-come-lately in big data. U.S. government funding of computing research in the 1940s and 1950s stretched from World War II’s radar/countermeasures battles to the elemental electronic intelligence (ELINT) and signals intelligence (SIGINT) research at Stanford and MIT, leading to the U-2 and OXCART (ELINT/image intelligence platforms) and the Sunnyvale roots of the National Reconnaissance Office.

Is Big Data the Way 
Ahead for Intelligence?

October 1, 2013

Another Overhyped Fad

By Mark M. Lowenthal

Director of National Intelligence Lt. Gen. James R. Clapper, USAF (Ret.), once observed that one of the peculiar behaviors of the intelligence community is to erect totem poles to the latest fad, dance around them until exhaustion sets in, and then congratulate oneself on a job well done.

One of our more recent totem poles is big data. Big data is a byproduct of the wired world we now inhabit. The ability to amass and manipulate large amounts of data on computers offers, to some, tantalizing possibilities for analysis and forecasting that did not exist before. A great deal of discussion about big data has taken place, which in essence means the possibility of gaining new insights and connections from the reams of new data created every day.

Or does it?

Read the complete perspective

A Longtime Tool of the Community

By Lewis Shepherd

What do modern intelligence agencies run on? They are internal combustion engines burning pipelines of data, and the more fuel they burn the better their mileage. Analysts and decision makers are the drivers of these vast engines; but to keep them from hoofing it, we need big data.

The intelligence community necessarily has been a pioneer in big data since inception, as both were conceived during the decade after World War II. The intelligence community and big data science always have been intertwined because of their shared goal: producing and refining information describing the world around us, for important and utilitarian purposes.

Read the complete perspective

AFCEA Answers: The Five "Vs" of Big Data

September 13, 2013
By Max Cacas

In considering how best to manage the challenges and opportunities presented by big data in the U.S. Defense Department, Dan Doney, chief innovation officer with the Defense Intelligence Agency (DIA), says the current best thinking on the topic centers around what he calls, “the five Vs”.

Appearing on a recent episode of the AFCEA Answers radio program, Doney says it’s important to always consider “volume, velocity, variety, veracity and value” when trying to manage and take advantage of big data.

“Volume gets the most attention,” he says, noting that most people focus on datasets measured in terabytes and petabytes. “In fact, though, that’s the one in which we’ve made the most progress. When it comes to “velocity,” or the rate at which large datasets often pour into servers, Doney notes that many algorithms originally designed for static databases now are being redesigned to handle datasets that require disparate types of data to be interconnected with metadata to be useful.

Doney goes on to say that “variety” remains one of the last three challenges when it comes to big data for his agency because of the DIA’s mandate to create a “big picture” that emerges from all that information. And he says that solutions have so far not caught up with the DIA’s needs.

Doney says “veracity,” or the “ability to put faith behind that data,” becomes a challenge when one needs to put equivalent amounts of context to disparate data types to add important detail to that “big picture.”
 

Brian Weiss, vice president, Autonomy/HP, says that when it comes to “value” in consideration of big data, some of the most exciting innovation is coming in terms of how to distinguish and sort out important information from the huge datasets.

Szykman: Turning Big Data Into Big Information

August 30, 2013
By Max Cacas

 
Current efforts to deal with big data, the massive amounts of information resulting from an ever-expanding number of networked computers, storage and sensors,  go hand-in-hand with the government’s priority to sift through these huge datasets for important data.  So says Simon Szykman, chief information officer (CIO) with the U.S. Department of Commerce.
 
He told a recent episode of the “AFCEA Answers” radio program that the current digital government strategy includes initiatives related to open government and sharing of government data. “We’re seeing that through increased use of government datasets, and in some cases, opening up APIs (application programming interfaces) for direct access to government data.  So, we’re hoping that some of the things we’re unable to do on the government side will be done by citizens, companies, and those in the private sector to help use the data in new ways, and in new types of products.”
 
At the same time, the source of all that data is itself creating big data challenges for industry and government, according to Kapil Bakshi, chief solution architect with Cisco Public Sector in Washington, D.C.
 
“We expect as many as 50 billion devices to be connected to the internet by the year 2020.  These include small sensors, control system devices, mobile telephone devices.  They will all produce some form of data that will be collected by the networks, and flow back to a big data analytics engine.”  He adds that this forthcoming “internet of things,” and the resultant datasets, will require a rethinking of how networks are configured and managed to handle all that data. 
 

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