Big Data

A Better Definition for Machine Learning

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Bill Franks of the International Institute for Analytics recently opined, “In recent years, the use of the term Machine Learning has surged. What I struggle with is that many traditional data mining and statistical functions are being folded underneath the machine learning umbrella. There is no harm in this except that I don’t think that the general community understands that, in many cases, traditional algorithms are just getting a new label with a lot of hype and buzz appeal. Simply classifying algorithms in the machine learning category doesn’t mean that the algorithms have fundamentally changed in any way.” Read more

RPI President Calls for Improved Data Analytics, Connectivity

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According to a recent article out of RPI, “Universities must make new and innovative connections to harness the full power and potential of this data-driven era, Rensselaer Polytechnic Institute President Shirley Ann Jackson said [Tuesday] in a keynote address at the Internet2 Global Summit in Denver, Colorado. Deriving ‘insights from the massive amounts of web-based data that humanity is producing about itself, during the ordinary course of every day…. may be the greatest intellectual challenge and opportunity we all face in academic life,’ President Jackson told the gathering of academic, business, and government leaders in the arena of information technology. ‘Today, we analyze less than 1 percent of the data we capture, even though the answers to many of the great global challenges lie within this overabundant natural resource,’ Jackson said. The challenge, she notes, is finding new ways to address the volume, velocity, variety, and veracity of the data.” Read more

Get a Grip on Big Data with ‘Content Intelligence’

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Jeremy Bentley of KMWorld recently wrote, “The age of the Internet has made us accustomed to having all the information we could want readily available at our fingertips – quite literally so, thanks to laptops, tablets, smartphones and other devices… Unfortunately, we rarely experience the same level of data accessibility in our workplaces, where internal information assets can be massive and hugely complex—and not at all easy to access search with the pinpoint precision that is usually required to find a very specific document or piece of content. Addressing this challenge should be high on the priorities list of any organization aiming to extract value efficiently from unstructured content. But it is proving to be no easy task.” Read more

Load-Control: Semantria Takes On The Social Media Surge Infrastructure Challenge

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Image courtesy: Flickr/Webtreats

Semantria is tackling some of the challenges that come with being a cloud-based social media services provider startup. The company offers a text and sentiment analysis service (which you can read about here) to clients and partners. That includes companies like Sprinklr, which manages the social customer experience for other brands with the help of Semantria’s API for analyzing social signals about those clients.

The good news is that with growing social data volumes, there’s a growing need for semantically-oriented services like Semantria’s that help businesses make sense of that information for themselves or their clients. The downside is that a huge surge in volume of social mentions around a company, its product, or anything else can hit such services hard in the pocketbook when it comes to acquiring the cloud infrastructure to handle the tidal wave.

“Everybody suffers from this kind of thing,” says Semantria founder and CEO Oleg Rogynskyy. “We experience it daily.”

Read more

Machine Learning’s Future: Fortune 500 Buys In, Manufacturing Sees The Light

STServerMartin Hack, CEO and co-founder of machine learning company Skytree, has a prediction to make: “In the next three to five years we will see a machine learning system in every Fortune 500 company.” In fact, he says, it’s already happening, and not just among the high-tech companies in that ranking but also among the “bread and butter” enterprises.

“They know they need advanced analytics to get ahead in the game or stay competitive,” Hack says. For that, he says, they need machine learning algorithms for analyzing their Big Data sets, and they need to be able to deploy them quickly and easily — even if those who will be doing the deployments are coming from at best a background of basic analytics and business intelligence.

“There just aren’t enough data scientists to go around,” he says. It’s very tough to fill those roles in most companies, he says, “so like it or not, we have to make it much, much easier for people to digest and use this.”

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Machine Learning: Why It Matters

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Martin Hack of Wired recently wrote, “When Amazon recommends a book you would like, Google predicts that you should leave now to get to your meeting on time, and Pandora magically creates your ideal playlist, these are examples of machine learning over a Big Data stream. With Big Data projected to drive enterprise IT spending to $242 Billion according to Gartner, Big Data is here to stay, and as a result, more businesses of every size are getting into the game. To many enterprise organizations Big Data represents a strategic asset — it reflects the aggregate experience of the organization. Each customer, partner, or supplier response or non-response, transaction, defection, credit default, and complaint provides the enterprise the experience from which to learn.” Read more

Bringing Connectivity to Your Data with Semantic Tech

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Last week, David Amerland of Forbes wrote, “At the heart of the semantic Web is connectivity. The key is the ability of one set of data to be connected to a different set of data—with fresh meaning arising from the connection. If that sounds like a souped-up version of the word-association game, you might ask, ‘So what?’ The value lies in the clarity of the picture that emerges… Consider that the BYOD trend that’s underway requires the development of trust inside the organization. Trust is needed not just as part of the natural evolution of the internal structure of the enterprise, but also for it to respond better and faster to marketplace events that can wrong-foot it. In other words, no business can expect to survive if it remains the same.” Read more

DataRPM Secures $5.1 Million in Series A to Advance Cognitive BI Platform

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FAIRFAX, Va.–(BUSINESS WIRE)–DataRPM, the industry pioneer in cognitive business intelligence, today announced that it has closed a $5.1 million Series A funding round. Led by InterWest Partners and joined by CIT GAP Funds, the round will be used to accelerate DataRPM’s global go-to-market strategy. DataRPM changes the way individuals work with data, making analytics more accessible and easier to use by solving the two main barriers to the adoption of data analysis – time consuming data modeling and usability. The DataRPM business intelligence (BI) platform removes those barriers, automating the data modeling process and employing a natural language question-and-answer interface to simplify data analysis and visualization. Read more

An Introduction to RAGE Semantic Intelligence Technology

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WESTWOOD, Mass., March 10, 2014 /PRNewswire/ – RAGE Frameworks, a provider of technology enabled solutions and services, introduces breakthrough Semantic Intelligence technology, integrated with its patented and model driven Business Process Automation platform.

 

The immense untapped strategic and operational potential buried in the body of information and knowledge in cyberspace continues to be a bridge too far, even in 2014.  So does the Real Time Intelligent Business Enterprise.  The technology to unlock the potential of Big Data and make it practical and applicable to drive new value for old [and new] businesses is still in its infancy, and lags the hype around Big Data by a great distance.  Read more

Twelvefold Introduces Spectrum for Video: Real-Time URL-Level Video Ad Placements Across All Screens

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San Francisco, Calif. (March 6, 2014) – Twelvefold, a big data company that targets audiences in real time without the use of cookies, today announced Spectrum for Video. Spectrum for Video delivers the most relevant video ad placements based on the influence, authority and emotional connection a piece of content creates with its reader. With more than 700 million individual videos from more than 5,000 sources, Twelvefold has culled and indexed the best of the web, including a mix of spot lengths. Read more

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