UPDATED 13:49 EDT / OCTOBER 31 2014

IBM wants to become a superpower in social media analysis

IBM CEO Ginni Rometty

IBM CEO Ginni Rometty

The marriage of Big Data with business intelligence is still evolving, but already it’s become an industry that’s worth multiple billions of dollars. Organizations are falling over themselves to transform their Big Data into actionable insights, and now IBM and Twitter Inc. are getting in on the act.

The partnership, which was announced earlier this week, gives organizations a way to make sense of Twitter’s firehose of data using IBM’s Watson supercomputer. The agreement also gives Watson access a rich new stream of real-time, real-world data it can use to beef up its own analytical skills and IBM a huge database of crowdsourced insight it can mine and sell to business function executives and vertical industries.

IBM says it will eventually launch a portfolio of Twitter analysis tools aimed at industries like banking, consumer products, retail and transportation. These will all come later, but for now, it’s going to integrate Twitter’s data stream into three of its existing: Watson Analytics, Watson Developer Cloud and its Bluemix Platform-as-a-Service (PaaS). IBM says that by using these services to mine Twitter, customer support, sales and marketing specialists will be able to “better engage and support their customers”.

“Twitter provides a powerful new lens through which to look at the world – as both a platform for hundreds of millions of consumers and business professionals, and as a synthesizer of trends,” said IBM CEO Ginni Rometty. “This is the latest example of how IBM is reimagining work.”

Under constant pressure from Wall Street investors to boost its financial results, IBM has been pursuing a deliberate strategy of shedding its commodity hardware businesses and transforming itself into a cloud-centric technology company. Big Data and Watson are a fundamental component of that plan, as IBM eyes the huge pile of cash enterprises are willing to spend on business intelligence.

One of the challenges for IBM is that the data analytics space, as young as it is, is also pretty crowded. Big Data analytics software and solutions are two-a-penny, and so even though it has the power of Watson behind it, IBM’s own products struggle to stand out from the crowd.

Social data can change that. Quite unlike the transaction data that most organizations collect off their own backs, social data is unstructured, it’s rapid-fire, it happens in real-time and it’s never-ending. And the general consensus is it can be extremely valuable if you know what to do with it.

“It’s forcing people to rethink and redefine the way they want to engage, whether it’s in a call center, operations or logistics,” said IBM’s Inhi Cho, VP & GM of Big Data, Insight and Governance in an interview on theCUBE during IBM’s Insight conference this week.

“We call it real-time context, being able to integrate new types of data like Twitter with enterprise data and marry that in a way that completely redefines the way you do sense-and-respond applications for operations, and the way you rethink the quality of your customer response so its not just reactive but much more proactive.”

*Continues after the video

IBM is by no means the first company to try to harvest Twitter as a real-world data source, but it’s the first one that’s thrown a supercomputer at the problem. It needs one, because social media analysis has historically proven to be a notoriously difficult task; the errors made by Google Flu Trends are a perfect example of how tricky it can be.

“The Internet of Things is going to continue to add more and more data, more blabber and babble, and you just don’t know if something’s relevant or not. It’s exceptionally difficult,” said Jeff Jonas, IBM Fellow and Chief Scientist, at IBM Insight 2014. “So what you have to do, the essence of context computing, is take the stuff that’s happening at the social ether as puzzle pieces, and to evaluate its importance and to who.”

And that’s where Watson comes in – it’s going to scour millions of tweets in real-time and try to pick out the ones that are important for each of its customers, based on the context, where it was tweeted from, and why.

“You’re looking at what was expressed, where they were and when, and you’re looking at what else is to happening to them, what else have they done,” adds Jonas. “Now when you see something happen you can see what else is happening around it, and you can use that to tell you whether or not that thing is important or not.”

photo credit: pasukaru76 via photopin cc

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