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Melanie Turek
Melanie Turek is Vice President, Research at Frost & Sullivan. She is a renowned expert in unified communications, collaboration, social...
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Melanie Turek | September 18, 2012 |

 
   

Social and Big Data: A Match Made in Heaven?

Social and Big Data: A Match Made in Heaven? The latest IBM Connections release combines the company's expertise in data mining with its more recent foray into social media to deliver valuable social analytics, as well as more evolved collaboration.

The latest IBM Connections release combines the company's expertise in data mining with its more recent foray into social media to deliver valuable social analytics, as well as more evolved collaboration.

Last week Frost & Sullivan held our annual Growth, Leadership and Innovation conference in San Jose, and one of the leading topics of interest was Big Data. Of course, the problem itself is not new--for as long as companies have been collecting information, they've been trying to catalog, search, and analyze it for maximum benefit. But with the rise of personal computers and then the Internet, big data suddenly became a big problem, with vendors like IBM defining the issue as one of three "Vs": Velocity, Variety and Volume.

Today, the problem continues to grow, thanks in no small part to the enormous amount of unstructured data accumulating in communications and social media applications and services. According to a survey of 586 senior executives by the Economist Intelligence Unit and SAS, Facebook's users create an average of 90 pieces of content each month, and roughly 294 billion e-mails are sent every day. Figuring out how to leverage that information is fast becoming the new Holy Grail for IT and data geeks alike. Whether the goal is to better connect employees, enable collaboration across and among companies, or take advantage of previously unseen market opportunities, understanding the meaning behind unstructured data, in particular, may just be the differentiator between successful companies and those that struggle for relevance in an increasingly data-driven world.

With its latest version of IBM Connections, the company is giving organizations the tools they need to start mastering at least some of this material. I've long been a fan of IBM Connections, which has been a leader in the internal-collaboration market for years (if not in terms of market share, certainly in terms of thought leadership and completeness). With this latest release, the vendor is combining its historic expertise in data mining with its more recent foray into social media to deliver valuable social analytics, as well as a more evolved set of collaboration capabilities.

The newest version makes it easy for users to see a single view of all their contacts and contact points, and take immediate action on new information from within an existing activity stream. It's also easier to share 3rd-party content, weigh in on others' posts, and access email and calendar capabilities from within the social interface. Users can search across all status updates and follow discussions via hash tags. Best of all, perhaps, are the enhanced reporting capabilities, which let administrators and other managers monitor adoption, as well as slice and dice the data for proactive use. Finally, the new software starts to bridge the gap between internal and external collaboration, letting employees jump on issues as soon as they are raised by customers or partners.

It's also worth noting that with this release, the vendor is making IBM Connections (not Notes) the foundational core of its collaboration suite. To my mind, that speaks volumes about where communications are headed: social rules, and will continue to do so in the future, with voice, video and conferencing acting as elements of a larger interactive ecosystem, rather than the other way around (adding social to voice, say).

Of course, as with all data analysis, the devil is in the details, and it remains to be seen just how effective IBM Connections will be for any given organization. But at least IBM is on the right track, helping all of us make more sense of the mountains of data piling up in the cloud, terabit by terabit, even as you read this (and even as this becomes part of the data stream).





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