November 2014

All posts from November 2014

Big Data & Analytics Heroes: Ben Snyman

by pm2net on November 25, 2014 , Comments Off on Big Data & Analytics Heroes: Ben Snyman

“Roof stability and effective support is quite a challenge,” declares Ben Snyman, VP of Underground Mining and Smart Services at Joy Global and this week’s Big Data Hero. “If the roof has a problem, production halts. We cannot afford to wait around for a report telling us there is a problem. We need to know in real time what’s happening underground. My team needs to continuously monitor conditions in order to dynamically change the course of action. In underground mining, a few minutes could be the difference between maximum efficiency or a work stoppage. “

Source: big data hub

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Taking a more refined approach to big data

by pm2net on November 24, 2014 , Comments Off on Taking a more refined approach to big data

Data refinement is one of the most important revelations in the big data market. The idea is simple: you want to take advantage of and use all sources of big data. But when each individual user needs only information relevant to them, what’s needed is a data refinery. It automatically cleans, matches, secures and profiles data—that’s what is meant by refinement.

Source: big data hub

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Velocity is now the competitive differentiator for big data

by pm2net on November 21, 2014 , Comments Off on Velocity is now the competitive differentiator for big data

In 2014, there were several important shifts that occurred in the world of big data that business executives around the globe cannot afford to ignore. These shifts are outlined in the new IBM Institute for Business Value study Analytics: The speed advantage – Why data-driven organizations are winning the race in today’s marketplace.” This is part one in a multi-part series in easy to consume bites focused on the findings and insights from this study.

Source: big data hub

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Cognitive computing: Programming the artificial mind

by pm2net on November 20, 2014 , Comments Off on Cognitive computing: Programming the artificial mind

When you want to take artificial intelligence out of the realm of imagination and poetry, and bring it squarely into practical reality, you need computational tools. The tools need to help your cognitive application developers write the leanest models possible. Developers need frameworks, languages and libraries for building and tuning neural networks and other cognitive constructs for most efficient parallel processing of individual data inputs and the outputs of the nodes within a vast artificial neural network. You can acquire these tools from various sources, such as IBM Watson Developer Cloud. And there are as many approaches for building computational applications that learn from data and automate cognitive processes as there are for building traditional application logic.

Source: big data hub

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Big Data & Analytics Heroes: David Vinson

by pm2net on November 18, 2014 , Comments Off on Big Data & Analytics Heroes: David Vinson

David Vinson, business intelligence and analytics lead at Nike, believe that There’s a lot of new data out there—in fact, we now have access to data from the entire supply chain (from provisioning materials to build the shoe, to actually delivering the shoe on the dock, to selling the shoe). Big data and analytics is the wave of the future for Nike, but how do we take that data and make it really useful?

Source: big data hub

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Facts may be dangerous, but context brings safety

by pm2net on November 18, 2014 , Comments Off on Facts may be dangerous, but context brings safety

“Just the facts ma’am” worked well for Joe Friday in the 1950s, however, in our big data world (where factoids pop up at incredible speeds, often with little warning) we need big data technology to help us bring the right context and act in the business moment. You can make big data make sense and discern which facts are relevant to you with IBM Context-Aware Stream Computing.

Source: big data hub

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