I'm excited that this Thursday I'll be joining Zach Hofer-Shall from Forrester Research, Michael Wu from Lithium, and David Carr from the Brainyard at InformationWeek to discuss the intersection of Big Data and social analytics at Enterprise 2.0 in Boston.
As David points out, Big Data and social analytics are among the most overused buzzwords in enterprise software today. We're going beyond the buzz and digging into the substance of what real business problems these technologies solve. Bottom line: the explosive growth in volume, velocity, and variety of enterprise data brings opportunities for businesses to extract new meaning and value.
The growthof Big Data is now merging with another key trend: the emergence of the enterprise social graph. Consumers today are bombarded with an ever-growing volume of information. Thanks to the innovation in the consumer technology space, new solutions from Amazon, Google, Facebook and Netflix have emerged with recommendation engines to map relevant data to consumer interests in advertising and marketing. There is a tremendous opportunity here to extend Big Data modeling and social analytics techniques to the enterprise thanks to Social Business Software systems.
As social applications are introduced inside enterprises, employee work and activity are available to watch and follow. These enterprise systems expose the minute by minute work of thousands of co-workers. They can show which teams collaborate, what their interests are, and the work they are currently focused on. This data is available for all the users in the company. When integrated with additional data sources both internal and external to the company, the same techniques that Netflix uses to recommend movies can be made to recommend the most important data in the enterprise. These technologies can funnel events from the back-end systems to the employees who are in the best position to take action on them. As a result, the walls between employees, partners and consumers are coming down. New, hybrid connections -- and by extension communities -- are forming in and between different stakeholders.
The enterprise social graph now includes, and increasingly requires, these dynamic relationships in getting business done, whether that's cooperative innovation between product designers and fans, collaborative problem solving between partners, or project silo-busting across orgs inside the enterprise. Those companies that can harness these relationships are finding a competitive edge over their rivals. It's the new way to business.
Social analytics and the science of relationships provide new ways to process and mine large scale, heterogeneous data, all of which are streaming at the speed of the Web. It's not just about monitoring the Social Web. It's about using new techniques to cut through the irrelevant noise in the enterprise to get work done. The future of work is personalized, giving people access to the right information and the right people at the right time, helping people weave their own new connections.
At Jive, we're working at the intersection of these powerful forces. We are bringing the best of consumer technology to the enterprise to change the way work gets done, increasing productivity while making work more fun and more personal. In the coming months, you'll see us using these techniques to power a new generation of smart, adaptive features in Jive, including supercharging our recommender, analytics, search and the Jive Social Media Engagement. All of this helps our customers unlock the value of the social graph in the enterprise and build the kind of critical social infrastructure that becomes a competitive advantage.
We'll explore some of these topics at our Enterprise 2.0 discussion this week. If you're at the show, join us on Thursday at 9:45 a.m. ET in Room 312!
As Jive’s Chief Social Scientist, David Gutelius is responsible for driving the enterprise social graph strategy. He was previously the CEO of Proximal Labs, a startup leveraging 'big data' for enterprise social networks that was acquired by Jive earlier this year. Prior to Proximal Labs, David was the co-founder and CTO at Social Kinetics. He additionally co-founded the Social Computing Group at SRI International's Aritificial Intelligence Center, and he served as the Product Manager on the DARPA CALO project -- the largest machine-learning project ever funded. David's background is in behavioral economics with a focus on social network theory. He was previously a visiting professor at Stanford University, and holds a Masters and PhD in economic history from Johns Hopkins.
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