According to Juniper Research, “A new report from Juniper Research forecasts that almost 50% of data traffic generated by mobile phones, tablets and other 3G/4G connected devices, will be offloaded to Wi-Fi and Small Cell networks this year. This is equivalent to 10 billion movie downloads or 9,000 petabytes (PB) per year being offloaded from mobile operator’s networks. The new report, Mobile Data Offload & Onload: Wi-Fi, Small Cell & Carrier-Grade Strategies 2012-2017, found that while Operators were benefiting from much needed relief on their over-stretched networks, they were potentially losing monetisation opportunities on the lost data usage.”

The article continues, “In response, Operators are actively partnering with existing Wi-Fi networks and launching their own carrier grade Wi-Fi solutions. In addition, 4G technologies such as LTE along with other wireless technologies are enabling Operators to provide new services and next generation connected devices such as smart glasses. Report author Nitin Bhas added: ‘While a 4G connection need not necessarily mean more data usage, consumers are in fact adapting to faster speeds and more data services, which could lead to more data usage. This increase in user demand for services in turn creates new opportunities within different economic sectors including commerce, energy, health and education, completing a cycle of demand’.”

Read more here.

Michael Hirsh of Quartz recently wrote, “Some of America’s biggest social media and tech companies have been denying in recent days that they were aware of the National Security Agency’s recently-exposed ‘PRISM’ and telephone monitoring programs. But these denials obscure a larger truth: The government’s massive data collection and surveillance system was largely built not by professional spies or Washington bureaucrats but by Silicon Valley and private defense contractors. So says Michael V. Hayden, the retired Air Force general who as director of the NSA from 1999 to 2006 was a primary mover behind the agency’s rebirth from Cold War dinosaur into a post-9/11 terror-detection leviathan with sometimes frightening technical and legal powers.”

Hirsh continues, “After many false starts, that transformation was achieved largely by drafting private-sector companies that had far more technical know-how than did the NSA, and contracting with them to set up and administer the technical aspects of these surveillance programs, Hayden told National Journal in an interview Sunday. ‘There isn’t a phone or computer at Fort Meade [NSA headquarters] that the government owns’ today, he says. That doesn’t quite square with the popular image of the NSA as a shadowy confection of Big Brother and Big Government. Nor with the description of PRISM as merely ‘an internal government computer system,’ as Director of National Intelligence James Clapper called it over the weekend.”

Read more here.

Justin Kern of Information Management recently reported, “In the background of ongoing revelations and fallout from a federal contractor leaking what are reportedly U.S. government scans of loads of private citizen phone data are enterprise lessons on approaching advanced analytics, big data and public information projects, according to industry experts. The personal data privacy concerns nor the government safety intentions with this unfolding data surveillance story are not to be taken lightly. But, as massive data volumes are increasingly sold on the business side as a silver bullet to find competitive advantage, there are takeaways for business uses of huge, nebulous data sets, according to the EIM and enterprise security experts we reached out to over the last few days.”

Kern continues, “Dr. Larry Ponemon, chairman and founder of Ponemon Institute, says such a massive dragnet of information is, ethics aside, the ‘perfect big data use’ because of the volume and variety of data, but also the wide-reaching and sometimes tangential connections. In research done by his advisory, issues of privacy remain a top consumer concern over the last eight years, Ponemon says. However, over that same time period, the notion of personal data being totally secure and outside of the government or business view – particularly with so much sharing over social networks – has eroded toward a ‘fatalistic’ consumer perspective on their own data.”

Read more at Information Management.

Chris Morris of CNBC reports, “Just a few years ago, meteorologists regularly shared an inside joke about forecasts: Anything beyond three days is a guess. But on the heels of this week’s disastrous tornadoes in Moore, Okla., and last October’s Hurricane Sandy, it has never been more critical to be able to forecast long range events. Big data analysis is turning the guesswork of yesterday’s meteorology into a more precise and predictive science. Several big data companies are focusing on long-term weather modeling, and have found that by identifying patterns, comparing them to current conditions and adding in a layer of predictive analysis, they’re able to confidently predict what’s to come weeks and even months in advance.”

Morris continues,”‘Today’s traditional forecasting models tend to break down in a week to 10 days because they can’t input every observed data piece from around the world,’ said John Plavan, co-founder and CEO of EarthRisk Technologies. ‘There’s too much chaos in the system.’ While it’s still virtually impossible to predict an event like this week’s tornado, the models and forecasts from big data companies can be extremely valuable to a variety of businesses, ranging from retailers to insurers, as they plan ahead.  EarthRisk, for example, focuses on the energy trading market. By focusing in on probability models for extreme heat and extreme cold, it can help investors profit in the futures market.”

Read more here.

Mindy Powers recently wrote an article for Forbes stating, “Across industries, organizations are collecting and using large sets of data to get a leg up on the competition. One industry that has been particularly aggressive at harnessing the power of data is the banking business. And it’s no wonder. In 2009, the McKinsey Global Institute estimated that U.S. banks and capital markets firms collectively had more than one exabyte of stored data. And, according to IDC Financial Insights, the volume of digital content is expected to increase this year from last by 48 percent… So, what kind of data is being collected? Believe it or not, banks are working to figure out how to store and mine videos, images, news and social media data to draw out accurate customer profiles.”

Powers continues, “Accurate profiles help banks improve customer experience and retention. The more banks know about customers, the more they can tailor solutions to meet customer needs. Mining data ‘tells us what the customer wants, not what we think they want,’ says James Gifas, U.S. head of global transaction services for RBS Citizens. Analyzing customer data also allows banks to spot any potential customer problems, improve management of customer accounts, engage in real-time dialogue with customers, and improve overall customer experience online and over the phone. On the flip side, harnessing Big Data also helps banks to identify and contain fraud and to comply with money-laundering rules and sanctions.”

Read more here.

IBM recently announced, “Ushering in a new era of cognitive computing systems, IBM today unveiled the IBM Watson Engagement Advisor, a technology breakthrough that allows brands to crunch big data in record time to transform the way they engage clients in key functions such as customer service, marketing and sales. Now businesses can better serve consumers with a cognitive computing assistant that learns, adapts and understands a company’s data quickly and easily, enabling users to have IBM Watson at work quickly, while increasing its knowledge and value over time.”

The article continues, “Two years after its triumph on Jeopardy!, the IBM Watson Engagement Advisor is a first of a kind system designed to help customer-facing personnel assist consumers with deeper insights more quickly than previously possible. Delivered through cloud-delivered services and online chat sessions, IBM Watson will empower a brand’s customer service agents to provide fast, data-driven answers, or sit directly in the hands of consumers via mobile device. In one simple click, the solution’s Ask Watson feature will quickly help address customers’ questions, offer feedback to guide their purchase decisions, and troubleshoot their problems.”

Read more here, or watch a video about the announcement here.

photo credit: IBM

Wyatt Kash of Information Week reports, “The CIOs of federal agencies are assessing the full scope of a White House executive order, introduced May 9, that requires agencies to make government data available in open, machine-readable formats. One likely outcome is that federal IT teams will have to give data sets the same of lifecycle management attention they already apply to hardware and software investments, said Simon Szykman, CIO at the Department of Commerce. ‘Data will be part of what gets addressed early on in the lifecycle [of new systems or applications],’ Szykman said during a May 14 presentation at the FOSE conference in Washington, D.C. ‘This makes it more systematic requirement and a bigger part of what we’ll be doing in the future’.”

Kash continues, “Szykman predicted the executive order will lead to ‘less ad hoc modeling and sharing and more systematic sharing of data,’ in response to questions about the policy. Richard Holgate, assistant director for science and technology and CIO at the Bureau of Alcohol, Tobacco, Firearms & Explosives (ATF), said the executive order is significant not only for making government data more readily available to the public, but also for sharing data internally between government components. The Department of Justice, of which ATF is one of many component organizations, publishes a variety of crime statistics that are useful to the public. But the majority of data it produces revolves around case files used by law enforcement agencies, attorneys, the courts, and other parts of the criminal justice system.”

Read more here.

Kristian J. Hammond of the Harvard Business Review recently wrote, “Evidence-based decision-making (aka Big Data) is not just the latest fad, it’s the future of how we are going to guide and grow business. But let’s be very clear: There is a huge distinction to be made between ‘evidence’ and ‘data.’ The former is the end game for understanding where your business has been and where it needs to go. The latter is the instrument that lets us get to that end game. Data itself isn’t the solution. It’s just part of the path to that solution. The confusion here is understandable. In an effort to move from the Wild West world of shoot-from-the-hip decision making to a more evidence-based model, companies realized that they would need data. As a result, organizations started metering and monitoring every aspect of their businesses. Sales, manufacturing, shipping, costs and whatever else could be captured were all tracked and turned into well-controlled (or not so well-controlled) data.”

She continues, “I would argue that what you want and what you need is to turn that data into a story. A story explains the data rather than just exposing it or displaying it. A narrative that gives you context to today’s numbers by exploring the trends and comparisons that you need in order to make sense of it all. The belief that Artificial Intelligence can support the generation of natural language reporting from data is what drove me to help found our company, Narrative Science. I fundamentally believe that a machine can tackle and succeed at freeing insight from data to provide the last mile in making big data useful, and this belief was the driver in building out a technology platform that makes it real.”

Read more here.

Paul Thorley of CIO.com reports, “Capgemini’s 2012 global survey on big data, commissioned by the Economic Intelligence Unit, covered 607 executives around the world (25 per cent in the Asia-Pacific region), and found that the majority of respondents (54 per cent) say that management decisions based purely on intuition or experience are increasingly regarded as suspect… With regard to the most valuable big data sets, there has been significant consensus across industries: 69 per cent of the participants agree that business activity data (sales, PoS data, purchases, etc) were the most valuable, followed by office documentation (emails, document stores, etc).”

“However,” he continues, “health care and pharmaceuticals differ, citing social media as the second most valuable big data set, possibly because of sentiment analyses reflecting consumer views and trends as keys to health care products. With unstructured data seen as the second most valuable big data set, more than 40 per cent of respondents said that unstructured content was too difficult to interpret and manage to be used in support of decision making. Interestingly, the survey also showed that many of the organisations that described themselves as being data driven felt that they could have made better decisions if the right data had been available… The research shows that organisations are also struggling with the enormous volumes of data as well as their poor quality, together with ‘silo’ed’ nature of dealing with data to drive decision making.”

Read more here.

Max Nisen of Business Insider reports, “Increasingly, recruiters and managers are going beyond the resume and evaluations and turning to Big Data. That means a lot of old practices for evaluating people and stereotypes about who succeeds are falling apart. Google, known for rigor in evaluating people, has devalued SAT scores and college GPA, which have long been critical tools for gauging potential. Prasad Setty, Google’s vice president for people analytics, told The New York Times that they’ve found that those numbers alone didn’t lead to success at the company, and ‘are no longer used as important hiring criteria.’ According to their data, the most innovative and happy workers feel like they have autonomy and a strong sense of mission, so Google looks for employees who have an entrepreneurial bent over those with the best test scores.”

Nisen goes on, “Those insights come from an incredibly detailed employee data tracking program, which tries to optimize everything from optimal levels of pay and benefits to the length of lunch lines. Data comes from the usual sources, surveys, employee feedback, and so on, but also from experiments from the company’s People & Innovation Lab designed to figure out best practices. Google applies that wealth of data to both hiring and management.”

Read more here.

photo credit: Google