Big Data and Cloud Computing

In my experience, there are two types of companies when it comes to big data: those who don’t want anything to do with it (because they think it’s for somebody else) and those who desperately want to implement, but don’t know where to start.   Regardless of where your company falls on that spectrum, there are several attitudes I encounter regularly that can kill a big data project faster than anything else.  Identifying and neutralizing these attitudes is key to getting a project off the ground and into implementation. We are not a data company. Every company is now a data company, and you’d better wake up to that fact. Data is everywhere and a part of everything, and I cannot think of a single industry or business that couldn’t benefit from understanding more about their customers, their sales cycles, demand for their product or service or their production inefficiencies. Just because you don’t  yet  know how big data could benefit your company, doesn’t mean...

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The following is a simple example of a much larger simulation that I want to run Define some processes norTheta [ mu_ , sigma_ ] := Random [ NormalDistribution [ mu , sigma ]] ; norPi [ mu_ , sigma_ ] := Random [ NormalDistribution [ mu , sigma ]] ; thetaNext [ thetaNow_ ] := thetaNow + ( - lambdaTheta * ( thetaNow - thetaBar ) * deltaT + sigmaTheta * norTheta [ 0 , 1 ] * Sqrt [ deltaT ]) ; piNext [ piNow_ , thetaNow_ ] := piNow + ( - lambdaPi * ( piNow - thetaNow ) * deltaT + sigmaPi * norPi [ 0 , 1 ] * Sqrt [ deltaT ]) ;   Then define some parameters   lambdaTheta = 0.07 ; thetaBar = 0.02 ; sigmaTheta = 0.012 ; lambdaPi = 1.0 ; sigmaPi = 0.0125 ;     Then simulate the system   steps = 252 ; T = 50 ; deltaT = 1 / steps ; // N Maturity = T * steps ; process = Transpose [ NestList [{ piNext [ # [[ 1 ]] , # [[ 2 ]]] , thetaNext [ # [[ 2 ]]]} &, { 0.02 , 0.02 } , Maturity ]] ...