Alex Pierre-Traves of Forbes reports, “The International Data Corporation (IDC) predicts the volume of data will grow by 40 percent over the next seven years. That’s a lot of data to manage, analyse and ultimately integrate into your business decisions. It’s unsurprising, then, to discover that analytics is the next big thing in marketing expertise. Today, data is used primarily to inform and analyse marketing campaigns, which is great for those of us in the agency business; however, what’s missing is meaningful analysis for our clients’ businesses to develop products and services that are relevant to their customers and, in turn, build brand loyalty. As the data we have at our disposal grows, new hires in marketing departments will increasingly need to have a technical, data or analytics background in order to deliver the strategic insights necessary for the business.” Read more

Lee Feigenbaum of Cambridge Semantics recently wrote, “The best thing about the Big Data hype in pharma is how effectively it’s shed light on all of the Small Data problems the industry is facing. The roots of the Big Data movement in pharma were innocent enough: challenges in storage, data access, and data analytics that organizations started seeing with shifts toward high-throughput screening and massive genomics data sets. But as Big Data became more and more mainstream, the range of business challenges that got slapped with the “Big Data” label started ranging further and further afield. Industry analysts noticed this quickly, redefining Big Data in terms of the three (or four) Vs–not just volume but also variety, velocity, and variability. Others have been quick to follow. At a recent conference on data-driven drug development, speaker after speaker stood up to talk about their approach to Big Data, and each speaker immediately qualified that they were speaking about the variety of data, rather than the volume of data.” Read more

Max Engel of HypeBot recently identified the smart use of data as one of three major trends currently shaping the future of product development. He writes, “The role that data plays goes beyond analytics. Open platforms and API’s allow for the creation of product mash-ups that have broken down barriers to content availability. One cannot underestimate the brilliance of platform-focused companies like SoundCloud and Spotify that allow innovation to occur rapidly and unfettered. Similarly, structured data is going to be increasingly impactful. Facebook’s Open Graph, for example, projects the foundation for the oft-mentioned semantic web.” Read more

Susan Watts of the BBC reports, “Government and companies now collect, store and analyse as much information as they can about the way we interact with them. Their goal is the pursuit of efficiency, and to find ways to save, or make, money. There is even a phrase for it – ‘big data’. The idea is not just to collect this data, but to analyse it. Take healthcare. In December 2012, the government announced a big data plan for perhaps our most intimate of data, the DNA read-out of 100,000 people with rare diseases and cancer. It is a colossal sequencing effort. Not only does each patient have a unique DNA code, but so do their cancer tumours. And some patients will respond to certain drugs better than others, depending on the genetic variants they carry.”

Watts goes on, “The claim is that a mass DNA database could herald a new era in medicine, and make the nation richer too. Read more

In the same way that Columbus “discovered” a New World that was already there, more businesses may be about to discover the world of semantic web technology that’s been there all along.

Photo credit: Flickr/torkildr

Their expeditions in this direction, not surprisingly, are likely to have a Big Data hook. In a recent survey, New Vantage Partners queried the connection, asking respondents, “What data structures and standards are of particular interest in your Big Data initiatives?.” It listing among the choices flat-file, relational, graphs, and yes, Semantic Web technology.

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Bryan Bell of Cogito reports that financial companies are wise to turn to semantic metadata for better Big Data analytics. Bell writes, “Financial institutions are looking to linguistics and semantics as the best option for managing and taking advantage of their unstructured data, using it to better understand customers and competitors, to identify impactful market trends or simply to automate the process of answering common customer questions. As one Chief Data Officer put it, ‘We are the stewards of one of our firms’ most important assets, data, and we have been charged with bringing meaning to the data. I believe semantics offers a consistent, long-term capability and change in how data will be managed’.” Read more

Kyield recently announced “a new pilot program for its recently patented semantic enterprise platform. The artificial intelligence system provides a holistic architecture that extends advanced business intelligence and predictive analytics to all information workers in the organization with an adaptive approach to data optimization.” Kyield CEO Mark Montgomery stated, “We are inviting well-matched organizations to collaborate with us in piloting our breakthrough system to bring a higher level of performance to the information workplace… In addition to the significant competitive advantage exclusive to our pilot program, we are offering attractive long-term incentives free from lock-in, maintenance fees, and high service costs traditionally associated with the enterprise software industry.” Read more

Deiter Bohn reports that Wolfram Alpha is now offering a “Pro” version of their data analysis services for just $4.99 a month: “The new services includes the ability to use images, files, and even your own data as inputs instead of simple text entry. The ‘reports’ that Wolfram Alpha kicks out as a result of these (or any) query are also beefed up for Pro users, some will actually become interactive charts and all of them can be more easily exported in a variety of formats. [The Verge] sat down with Stephen Wolfram himself to get a tour of the new features and to discuss what they mean for his goal of ‘making the world’s knowledge computable.’” Read more

Chris Talbot recently argued that the semantic web is and will be instrumental to the effective analysis of Big Data. He writes, “As big data stores continue to grow and require additional management, enterprises are faced with the task of managing their explosive data growth while also trying to find the best way to analyze that data. According to the recent InformationWeek ‘Database Discontent’ report, a top item on IT departments’ 2012 to-do list is handling big data in a way that allows for change over time.” Read more

Jeff Stamen of Cambridge Semantics has questioned whether Big Data is worth the hype or if the tech headlines should actually be touting Right Data. Stamen writes, “One look at all the IT headlines these days would suggest that Big Data is the most important data issue today. After all, with lots of computing power and better database storage techniques it is now practical to analyze petabytes of data. However, is that really the most compelling need that end users have? I don’t think so. Instead, I would claim that the issue most end users have is getting together the right data to help them do their jobs better, not analyzing billions of individual transactions.” Read more