The Final Four of the Smart Sixteen Big Data Challenge
The stage has been set for the Final Four of the IBM Smart Sixteen Big Data Challenge. Starting with a field of 16 business uses of big data, the cream of the crop continues to rise. Last week, Natasha Gabriel listed the elite eight who made it past the first stage. Here is how the bracket is stacking up after another round of head-to-head matchups.
Predict Customer Behavior (PCB), without even breaking a sweat, easily handled Improve Campaign Effectiveness (ICE). With cheers from the crowd of their adoring fans, PCB outmaneuvered and outgunned ICE. Saying that PCB is a superstar performer is an understatement. I believe that PCB is the team to beat in this contest.
On a separate court, the rising star of Simplified Data Management (SDM) squeaked by Analyze Machine Data (AMD). Simplify Jr., the star player for SDM, openly mocked the complexity of the algorithms supporting AMD’s game plan. I’m interested to see how SDM will fare in the next round.
In the IT region, Real-time Streaming Data (RSD) made a superb showing against their nemesis, Enterprise-wide Integration, outscoring them by double digits. After giving RSD a second look (thanks to Twitter trash talking by David Pittman), I would not be surprised if they make it to the final game.
In a shocking upset, Reduced Resource Costs (RRC) put up six 3-point shots late in the game against Governance & Risk Management (GRM). Following tradition, GRM coaches played a very cautious, low-risk game, which analysts say is to blame for their poor showing against RRC. You really can’t win a game only shooting layups.
The Final Four of the “Big Data Smart Sixteen”
It has come down to these final four teams:
Predict Customer Behavior vs. Simplified Data Management
Real-time Streaming Data vs. Reduced Resource Costs
Who is going to take it all?
Other related posts
- View and download the brackets for the Final Four - Would you have made different selections?
- Join us for two special events on Big Data at the Speed of Business