Bernard Marr recently wrote, “It’s been estimated that by 2015, almost two million people will be employed in big data jobs in the US. Hal Varian, Google’s chief economist, is quoted as saying “…the sexy job in the next 10 years will be statisticians” and Tom Davenport, Distinguished Professor at Babson College, believes that a data scientist has the sexiest job of the 21st century. So what are these sexy jobs? Here’s a quick look at some of the positions available today that might allow you to break into the glamorous and exciting world of the big data professionals.” Read more
Greg MacSweeney of Wall Street and Tech recently wrote, “It’s relatively easy to find information on public companies. Bloomberg, Thomson Reuters, and Dun & Bradstreet, for example, all have in-depth information that is accessible to anyone with a subscription. But where do investment bankers, venture capitalists, and other investors find reliable information about private companies? If you talk to investment bankers, or other investors who are looking for information on non-public companies, it quickly becomes apparent there is no easy answer. Investment bankers rely mostly on Google searches and a combination of information gathered from Hoovers, S&P Capital IQ, Dun & Bradstreet, and others. But it is a laborious manual process to do due diligence on private companies.” Read more
Janet Wagner of Programmable Web reports, “FirstRain, a personal business analytics platform provider, has announced the launch of a FirstRain API that allows enterprise developers to incorporate FirstRain platform functionality into third-party applications and systems. The new FirstRain API provides programmatic access to real-time data from the proprietary FirstRain business graph, which the company says ‘extracts the deep, interconnected relationships between companies, businesses and markets’.” Read more
Ron Miller of TechCrunch reports, “IBM today announced a new product called Watson Analytics, one they claim will bring sophisticated big data analysis to the average business user. Watson Analytics is a cloud application that does all of the the heavy lifting related to big data processing by retrieving the data, analyzing it, cleaning it, building sophisticated visualizations and offering an environment for communicating and collaborating around the data. And lest you think that IBM is just slapping on the Watson label because it’s a well known brand (as I did), Eric Sall, vp of worldwide marketing for business analytics at IBM says that’s the not the case. The technology underlying the product including the ability to process natural language queries is built on Watson technology.” Read more
Big Data has been getting its fair share of commentary over the last couple months. Surveys from multiple sources have commented on trends and expectations. The Semantic Web Blog provides some highlights here:
- From Accenture Anayltics’s new Big Success With Big Data report: There remain some gaps in what constitutes Big Data for respondents to its survey: Just 43 percent, for instance, classify unstructured data as part of the package. That option included open text, video and voice. Those are gaps that could be filled leveraging technologies such as machine learning, speech recognition and natural language understanding, but they won’t be unless executives make these sources a focus of Big Data initiatives to start with.
- From Teradata’s new survey on Big Data Analytics in the UK, France and Germany: Close to 50 percent of respondents in the latter two countries are using three or more data types (from sources ranging from social media, to video, to web blogs, to call center notes, to audio files and the Internet of Things) in their efforts, compared to just 20 percent in the UK. A much higher percentage of UK businesses (51 percent) are currently using just a single type of new data, such as video data, compared with France and Germany, where only 21 percent are limiting themselves to one type of new data, it notes. Forty-four percent of execs in Germany and 35 percent in France point social media as the source of the new data. About one-third of respondents in each of those countries are investigating video, as well.
Apigee wants the development community to be able to seamlessly take advantage of predictive analytics in their applications.
“One of the biggest things we want to ensure is that the development community gets comfortable with powering their apps with data and insights,” says Anant Jhingran, Apigee’s VP of products and formerly CTO for IBM’s information management and data division. “That is the next wave that we see.”
Apigee wants to help them ride that wave, enabling their business to better deal with customer issues, from engagement to churn, in more personal and contextual ways. “We are in the business of helping customers take their digital assets and expose them through clean APIs so that these APIs can power the next generation of applications,” says Jhingran. But in thinking through that core business, “we realized the interactions happening through the APIs represent very powerful signals. Those signals, when combined with other contextual data that may be in the enterprise, enable some very deep insights into what is really happening in these channels.”
With today’s announcement of a new version of its Apigee Insights big data platform, all those signals generated – through API and web channels, call centers, and more – can come together in the service of predictive analytics for developers to leverage.
What best practices should inform your company’s text analytics initiatives? Executive Lessons on Modern Text Analytics, a new white paper prepared by: Geoff Whiting, principal at GWhiting.com and Alesia Siuchykava, project director at Data Driven Business provides some insight. Contributors to the lessons shared in the report include Ramkumar Ravichandran, Director, Analytics, at Visa and Matthew P.T. Ruttley, Manager of Data Science at Mozilla Corp
One of the interesting points made in the paper is that text analytics can be applied to many use cases: customer satisfaction and management effectiveness, product design insights, and enhancing predictive data modeling as well as other data processes. But at the same time, a takeaway is that it is better for text analytics teams to follow a narrow path than to try to accommodate a wide-ranging deployment. “All big data initiatives, and especially initial text analytics, need a specific strategy,” the writers note, preferable focusing on “low-hanging fruit through simple business problems and use cases where text analytics can provide a small but fast ROI.
Customer experience management vendor Clarabridge wants to bring the first-person narrative from call center interactions to life for marketing analysts, customer care managers, call center leaders and other customer-focused enterprise execs. With its just released Clarabridge Speech, it now brings via the cloud a solution that integrates Voci Technologies’ speech recognition smarts with its own capabilities for using NLP to analyze and categorize text, sentiment and emotion in surveys, social media, chat sessions, emails and call center agents’ own notes.
Agent notes certainly are helpful when it comes to assessing whether customers are having negative experiences and whether their loyalty is at stake, among other concerns. But, points out Clarabridge CEO Sid Banerjee, “an agent almost never types word for word what the customer says,” nor will they necessarily characterize callers’ tones as angry, confused, and so on. With the ability now to take the recorded conversation and turn it into a transcript, the specific emotion and sentiment words are there along with the entire content of the call to be run through Clarabridge’s text and sentiment algorithms.
“You get a better sense of the true voice of the customer and the experience of that interaction – not just the agent perspective but the customer perspective,” Banerjee says.
IBM Taps Global Network of Innovation Centers to Fuel Linux on Power Systems for Big Data and Cloud Computing
CHICAGO, Aug. 22, 2014 /PRNewswire/ — At the LinuxCon North America conference last week, IBM (NYSE: IBM) announced it is tapping into its global network of over 50 IBM Innovation Centers and IBM Client Centers to help IBM Business Partners, IT professionals, academics, and entrepreneurs develop and deliver new Big Data and cloud computing software applications for clients using Linux on IBM Power Systems servers. Read more
Gil Press of Forbes reports, “Gartner released last week its latest Hype Cycle for Emerging Technologies. Last year, big data reigned supreme, at what Gartner calls the ‘peak of inflated expectations.’ But now big data has moved down the ‘trough of disillusionment’ replaced by the Internet of Things at the top of the hype cycle. In 2012 and in 2013 Gartner’s analysts thought that the Internet of Things had more than 10 years to reach the ‘plateau of productivity’ but this year they give it five to ten years to reach this final stage of maturity. The Internet of Things, says Gartner, ‘is becoming a vibrant part of our, our customers’ and our partners’ business and IT landscape’.” Read more