Subcribe to blog


Shawn Rogers - Blog


IBM Leads the Patent Race in 2013

Mashable has published coverage of the world wide patent race underway at leading technology companies. IBM maintains its first place position.

Read the Mashable article here.


The 5 Laws of Big Data Startup Analyst Briefings

These Big Data Laws are written for the entertainment and perhaps education of vendors who are in this market and are briefing the analyst community about their solution. I Hope it helps and makes you laugh just a little bit.

Law #1 - The heavier the marketing message the lighter the technology.

Companies that lead with buzz words and marketing blather generally are struggling to deliver on the technology front. Decide early if you want to sell a marketing message or an innovative technology that will solve enterprise challenges. Sell the value not the message and stay away from marketing slogans like - Hadoop is Free!! (My POV - Its free like a puppy.)

Law #2 - The proper answer to the question "How many customers do you have?" is a numeric value.

The improper answer is anything that doesn't start with a number. The worst answer is a long convoluted narritive on how you are serving the needs of many industry segments while focusing on premier client penetration thru value added partner channels within high opportunity niche markets...blah blah blah. If you can't or won't provide a number I already know its less than 10 and I'm nervous it might be zero. I can't recommend you to my clients if I think they might become an experiment.

Law #3 - You are not the first, you are not the only and do have competitors.

Statements like these make analysts crazy and we come away thinking that you don't really understand the competitive terrain or the market in general. Steer clear of these types of declarations and focus on how you provide value and solve real business problems. (See Law #1 for clarification)

Law #4 - Analysts already know Big Data is really, really, really big and so do your prospects.

The size of today's data is old news. I already know what a Petabyte, Zettabyte and a Yottabyte are. I know about machine data, dark data, The Internet of Things, social data and sensor data. Big Data is about opportunities, being able to do workloads we could only dream of doing years ago at a speed and economic level that now makes it practicle. Educate us on what your company does and how you do it, lets skip the part where you explain how the world produces more data daily than the contents of the Library of Congress.

Law #5 - A connector to Hive is not a comprehensive Big Data strategy.

Hive is an interesting access point to Hadoop data, the ability to pass SQL into Hive opens the door for some interesting functionality but its not a comprehensive Big Data feature set. Hive is the low hanging fruit of Hadoop interaction and was the starting point for many vendors who needed/wanted to add a Big Data marketing message to their go-to-market strategy. (See Law #1 for clarification)

Stay tuned for more Laws and updates to this post - 


Portability in a Hybrid Data Ecosystem

Adoption of the Hybrid Data Ecosystem continues to grow. Vendors are working to deliver highly integrated ecosystems with platforms that provide the user an agile and flexible array of solutions to address today's complex and demanding workloads. The interesting part of the story is the division in how they approach this opportunity. Some vendors are building fully featured "Walled Garden" style solutions with all parts dependent upon one another. Its a nice strategy that may lead to better inetegration but you can't really get away from it once you are engaged. This type of lock-in to technology and infrastruture can be dangerous and in the long run very expensive for the consumer.

Others (only a few) are focusing on highly integrated environments that match the competition feature for feature but at the same time allow for portability. Pivotal is a company working to bring its clients portability with cloud infrastructure. A common fear of cloud adaptors is being locked into one infrastructure provider for the duration of their projects or forever. If you utilize Pivotal on its Cloud Foundry platform you have the ability to move from AWS to Rackspace if need be providing a level of flexibility that most companies would prefer over time. This strategy is also smart for companies that suspect a Cloud based program may migrate back behind the firewall at some point. Being locked-in to a Cloud provider will make this an impossible change or at the least terribly expensive.

So this begs the question, what's better? Walled gardens or portable infrastructure. The answer seems obvious to me but I'm interested to hear from you on this topic.


DataSift Raises 42 Million "C" Round

DataSift a leading Social Data aggregator has raised additional capital of 42 million in a "C" round investment. The round was lead by Insight Venture Partners, with participation from existing investors Scale Venture Partners, Upfront Ventures, IA Ventures, Northgate Capital, Daher Capital and Cendana Capital. 

The social data distribution space has been very active this past few weeks. Apple purchased Topsy in early December leaving Gnip and Datasift as the last remaining companies with licence agreements with Twitter for distribution of thier social data stream. 

See TechCrunch Coverage of this story here.


Apple Acquires Social Data Firm - Topsy Labs

Apples purchase of Topsy this past week caught many analysts and social data experts by surprise.  This was an unexpected move on Apple's part as they have not been successful or aggressive in their social data strategy.  Apple hasn't had much to say on the acquisition and while $200 million is the reported purchase price it's a relatively small purchase by Apple standards. Wall Street liked the deal and Apple stock got a bump up on the news last week.

Comments from CEO Tim Cook in 2012 indicated that social expertise and strategy were on the agenda for Apple. At the all Things D conference he stated that Apple planed to integrate with other social networks rather than build its own and Apple needed to be social, because it doesn't have to own a social network.

 I don't suspect that Apple will use Topsy's database of 450 billion tweets dating back to 2006 to launch a social network. That ship has sailed and unless Apple could creat a new value proposition for that space they are best left to leveraging social data not creating it.

Apple has a vast database of customers and mountains of historical content use data, purchasing data and behavior data that they could enrich with social data to creat better and smarter product offerings.

 I would watch for the following to be powered by the Topsy acquisition.

  • Delivering more targeted ads on iTunes Radio and to the iAd platform
  • Using social data to drive more accurate content to users
  • Enhancing search with social data to increase relevancy 
  • Acquire-hire of the Topsy engineer team for faster social driven R&D
  • Using social signal to better deliver app's
  • Increase insight on users and share information with advertisers

Datasift and GNIP remain in the market as competitors to Topsy and I wouldn't be surprised to see another acquisition soon.