Subcribe to blog

Loading..

Shawn Rogers - Blog

Entries in Big Data (7)

Sunday
Aug212016

Analytic Lessons Learned From the Big Game

Proof that analytics is in every part of our lives, even american football. There are a few take aways from the sport that can be applied to analytics.

  1. Get the Jump 
  2. Win on the Edge
  3. Improve Upon What’s Already Working
  4. Change Your Culture
  5. Don’t Dismiss Intuition

I contribute regularly to CMSWire here is a link to the article "The Denver Broncos Analytic Game"

 

Wednesday
Sep092015

Opening the doors of Big Data Innovation

When I first got into this business, it was enough to figure out how many widgets were sold in a particular region. Now, companies want to know how many widgets were sold in a particular region, in a certain color, to a specific customer, 10 minutes ago. Or, even better, they want to be able to predict the result before it happens. This takes a different approach to information—one that requires IT and business people to be in lockstep before opening the data floodgates....

I often blog as the Chief Research Officer for Dell Software - Read this entire post on Dell.com

Tuesday
Jan212014

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 yes...you 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 - 

Friday
Jan172014

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.

Monday
Dec022013

Big Data and Health Care

An excellent story from the Huffington Post about Dr. Patrick Soon-Shiong. He's doing incredible things with data to solve cancer treatment challenges. The full article is available here -  "Meet Dr. Patrick Soon-Shiong, The LA Billionaire Reinventing Your Health Care".