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Cognitive computing
Big data and cognitive computing–Part 2

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We turn now to how the terms “big data” and “cognitive computing” are working on the symbolic level. We need to recognize first that when terms or phrases become buzz labels for entire new phases in the development of the computing business and the information economy, they take on something of a life of their own.

For example, simply by looking at the impact of the phenomenon of big data on the marketplace, we see a remarkable difference between the attitude and language of companies that actually run their businesses on big data and those companies that are using the terms but are primarily worried about being left behind.

Big data as raw material

Google, Facebook, Yahoo, Amazon—those are the firms that first encountered big data and learned how to harness it into Web advertising, social media, digital publishing and online commerce and Web services respectively. But those firms rarely make a big noise about the term “big data.” They view data as being simply raw material for business propositions that drive well beyond the narrow view of the technologies that underpin them. Those firms don’t view themselves as being in the computing business, despite the fact that they have invented the state-of-the-art tools and practices required to cope intelligently with massive volumes of flowing data. (An exception, of course, is Amazon’s cloud business, which offers its expertise and resources directly to others as a service.)

On the other hand, the legacy enterprise software vendors who dominated computing markets in the recent past have been trumpeting about “big data” loud and long. IBM (ibm.com), Oracle (oracle.com), HP (hp.com), Microsoft (microsoft.com), SAP (sap.com), EMC (emc.com)—all those firms missed the industry turn to cloud computing, software-as-a-service and big data, and are re-engineering their product lines and marketing approaches around the new terminology.

At this stage of the maturing of the big data marketplace, most analysts are predicting a slowing of innovation, a period of consolidation and a converging of big data offerings on a broadly comparable suite of products and services from a smaller number of vendors. In that environment, all the legacy vendors now need to differentiate their big data value. Enter cognitive computing.

R&D and marketing prowess

IBM deserves special mention in the discussion of the symbolic importance of the cognitive computing term, because the company has been years ahead of competitors in uniting its R&D in cognitive technologies with its event marketing prowess (Watson playing JEOPARDY!) and with a serious, long-term, multilayered business and investment initiative. It deserves recognition for proposing and successfully establishing the term in the first place. That said, IBM recognizes the value of cognitive computing in the short term in giving the company symbolic differentiation from its competitors in the trenches of the big data, cloud and analytics marketing wars.

We have left the consumer out of this discussion altogether, but we can’t close without noting that cognitive computing is now operating, for better and for worse, on your smartphone homescreen, and Apple (apple.com), Google, Microsoft and Amazon are betting that their nascent digital assistants will take over a greater and greater part of the operating interfaces of those devices. IBM and Apple have announced alliances around those emerging capabilities, and we will certainly see another round of consumer-driven IT arrive in the near term, with smarter “cognitive” applications delivered in mobile form factors available at work as well as in civilian life. And leveraging big data to boot!

In closing, we hope that we have offered perspectives on big data and cognitive computing that provide food for thought, a degree of clarity about similarities and differences, and a framework for looking at these fascinating and emerging technology trends with confidence and a level of immunity from industry hype.

 

Cognitive computing is in its earliest stages, with very few products even ready for the market and many more promises in the air than tangible results on the ground.

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