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MIT System Design and Management Conference: A Systems Approach to Big Data: Going Beyond the Numbers
Chris Miyachi
DEC 08, 2013 16:03 PM
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I attended a conference about Big Data at MIT on Thursday October 10th, 2013.  I am a graduate of the MIT System Design and Management program and every year, the SDM program hosts a conference on system thinking.  This year, the conference was focused on Big Data.

 

All the conference videos and slides can be seen here:  http://sdm.mit.edu/systemsthinkingconference/2013/speakers.html .

 

The first lecture I attended was by Troy Hamilton and was titled "A Holistic Approach to Integrating Big Data and Strategy: Lessons from the Financial Services Industry".  Troy has worked managing IT for financial services for his entire career.    He pointed out that it is  one of the most regulated industries in the world.  Ninety-five percent of all transactions are done electronically.    The number of transactions that occur on a trading day is so large that to remove even small costs per transaction change the bottom line. 

 

His main design goal was "simple is better".   Much of the changes he sees involves going to open source and partnering with customers IT infrastructure yet maintaining all the security necessary in a regulated system.  One of the new initiatives he was working is "Tick as a service" which provides market data aggregated for companies.

 

His presentation had some interesting case studies and I encourage you to take a look.

 

I also attended a panel discussion on "Leveraging Big Data for Business Value".   Big Data is already being used in business in a number of instances.   One way is when your credit card is rejected when you purchase something unexpected.  The credit card company has data analytics that look and find possible fraud detection immediately.  Another case is the way data is gathered on large engines to do predictive maintenance.  But there is another major part, which is the data science part.  We are able to measure things we haven't been able to measure before.  The panel pointed out we are in the verge of a major revolution in business as data science develops. 

 

There were other presentations I missed that I am able to watch and all of it was worthwhile.  

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