Big Data Monetization Sand Hill Road Conversations in Silicon Valley

Reed Smith’s Silicon Valley big data partner Bob Stefanski is putting on a big data event on Sand Hill Road in the heart of the VC capital of the world.

I will be on a panel with the following big data experts – Ram Menon is the President of Social Computing and Chief Marketing Officer at TIBCO Software; MC Srivas is the founder and CTO of MapR, and Steve Sommer the CMO of Splunk.  We will be talking about the industry trends around the technology and how it’s being monetized.

See agenda below.

I will be speaking from my experience working in the vertical and as the cofounder of VDP Finder, Inc – a product called vFinder(tm) a  Hadoop Hbase stealth startup that I founded when I was hanging out at Cloudera Labs in 2010.   Some sample output from our Hbase big data venture is here.  http://www.slideshare.com/siliconangle

I’ve shared my talking points below on what I will be talking about.

My Angle on Big Data – My Talking Points

What is Big Data?

Big data is any data that is too big or too diverse or too fast that requires non-traditional methods to store, retrieve, process and manage. Check out Wikibon’s definition of Enterprise Big Data.  http://wikibon.org/wiki/v/Enterprise_Big-data

Looking at the kinds of unstructured data that are driving the Big Data phenomenon – mobile (including location data), ‘social content’, Web e-commerce, enterprise data, embedded sensors (“Internet of Things”) & machine data etc – is any one kind of data more important than the others? Why or why not?

Value is in the eye of the beholder. To a financial services organization it’s fraud detection or risk management, to healthcare its data that can save lives to the energy industry it’s data that can find fossil fuels faster and more accurately, in retail, to advertisers its data that can be acted upon before you lose the customer in logistics it’s ways to take waste out of the supply chain, in government it’s finding bad guys. IT’s all valuable – it just depends on your perspective and your priorities.

What are the key enabling Big Data Technologies? What does each do and why is it important?

Platforms, tools, applications and visualization. Most interesting: 1) new storage technologies like hadoop that eliminate the reliance on legacy, monolithic ‘containers.’ 2) new platforms that bring together unstructured and structured data and batch and real-time—natively; 3) tools that help real business users visualize the data

Example of how you are helping a customer use Big Data to make money?>

We are using big data to find new customers for our clients. We use predictive analytics to find great stories to write about and connect with. Identify who is ready to buy? What’s their profile? What offerings to put in front of them. This is just a sample.

What sectors do you think are doing the best job right now utilizing Big Data to directly monetize and/or obtain competitive advantage? Why?

Yes, yes, yes and yes…look – here’s the bottom line – big data is the new source of competitive advantage. How organizations use data is going to set the bar in terms of who gets the richest or is the most effective (in the case of gov’t and healthcare).

The bottom line is big data practitioners – those that monetize data – are going to create more value than those who sell big data technologies. So while billions will be made by the companies who supply big data technology, trillions in value will be created by the users of big data tech.

Where do you see the greatest potential for Big Data to disrupt a particular industry’s business model?

There really isn’t an industry that won’t be disrupted by data. It’s always about how to create the most value in the shortest period of time – it’s the tradeoff between speed to market and effectiveness of solution – there’s a balance and striking that balance is part art part science.

Regarding these challenges, in particular around the collection and use of data generated from individuals such as consumers or employees, what do you see as the greatest challenges?

People will give to get. Don’t enable location services on your smart phone and you won’t get as much value out of it. Trade some privacy for a better user experience.

The biggest challenges are 1) managing the diversity of data – how to put structure into unstructured data 2) How do draw conclusive inference and take definitive action from ‘fuzzy’ data and 3) how to package, price, distribute and monetize the data.

Looking out over the next ten years, is Big Data the ‘Next Big Thing’? Why or why not?

“Data is the new oil” – says it all

How company’s use data will become the single most important factor in their success or failure.

Bottom line: this is a growth market across the board.  It’s the biggest disruption that I’ve seen since the PC revolution and client server computing COMBINED.

Exciting times.

Here is the official agenda

Agenda:
Kickoff – Bob Stefanski

Industry Panel – How Big Data is being monetized today.
Ram Menon, President of Social Computing, TIBCO
Steve Sommer, Chief Marketing Officer, Splunk
John Furrier, Founder & CEO, Silicon Angle
M.C. Srivas, Founder, MapR
Moderator: Bob Stefanski, Partner, Reed Smith

Privacy Panel – Big Data security and privacy
Mark Melodia, Partner, Reed Smith
Cynthia O’Donoghue, Partner, Reed Smith
Rebecca Kuehn, Vice President, Senior Regulatory Counsel, CoreLogic
Christopher Sundermeier, General Counsel, Reputation.com
Moderator: Chris Gill, CEO and Executive Director, SVForum

Venture Panel – The future of Big Data
Jake Flomenberg, Venture Capitalist, Accel Partners
Matt Ocko, Co-Managing Partner, Data Collective
Gregory La Blanc, Lecturer in Finance, Strategy and Law, Haas School of Business, University of California
Moderator: Don Reinke, Partner, Reed Smith

About John Furrier

Founder and CEO of SiliconAngle.com.

One Response to Big Data Monetization Sand Hill Road Conversations in Silicon Valley

  1. Dipesh says:

    Exicting developments. The Big Data world needs to be split into two: Big Data Infrastructure and Big Data Applications. The plumbling is key to make the apps run. But I predict their will be significant shift in value from BGI to BGA. The BGI will be context agnostic bit pusher and BGA will be BGI-agnostic but context-sensitive analysis and prediction capability that will grow into a true BD platform. I expect all BGI plays to start building vertical apps or else they graduate from vulnerable-to-threatened-to-endangered-to-extinct rather soon. The last mile of BD is BGA. And this is where value will be exploited.

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