A Quote by Douglas Merrill
Big data isn’t about bits, it’s about talent.
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With too little data, you won't be able to make any conclusions that you trust. With loads of data you will find relationships that aren't real... Big data isn't about bits, it's about talent.
We get more data about people than any other data company gets about people, about anything - and it's not even close. We're looking at what you know, what you don't know, how you learn best. The big difference between us and other big data companies is that we're not ever marketing your data to a third party for any reason.
Big data is great when you want to verify and quantify small data - as big data is all about seeking a correlation - small data about seeking the causation.
Every day, I absorb countless data bits through emails, phone calls, and articles; process the data; and transmit back new bits through more emails, phone calls, and articles. I don't really know where I fit into the great scheme of things and how my bits of data connect with the bits produced by billions of other humans and computers.
Where big data is all about seeking correlations - and thus to make incremental changes - small data is all about causations - seeking to understand the reasons why.
I don't like talking about which bits I like or don't like about my body. Everybody has something they're not happy with, and my only advice would be, 'Do something about it - exercise or eat less, but don't do nothing!' Find ways to enhance the good bits and camouflage the bad bits.
MapReduce has become the assembly language for big data processing, and SnapReduce employs sophisticated techniques to compile SnapLogic data integration pipelines into this new big data target language. Applying everything we know about the two worlds of integration and Hadoop, we built our technology to directly fit MapReduce, making the process of connectivity and large scale data integration seamless and simple.
Big data is mostly about taking numbers and using those numbers to make predictions about the future. The bigger the data set you have, the more accurate the predictions about the future will be.
The big thing that's happened is, in the time since the Affordable Care Act has been going on, our medical science has been advancing. We have now genomic data. We have the power of big data about what your living patterns are, what's happening in your body. Even your smartphone can collect data about your walking or your pulse or other things that could be incredibly meaningful in being able to predict whether you have disease coming in the future and help avert those problems.
The first wave of the Internet was really about data transport. And we didn't worry much about how much power we were consuming, how much cooling requirements were needed in the data centers, how big the data center is in terms of real estate. Those were almost afterthoughts.
People think 'big data' avoids the problem of discrimination because you are dealing with big data sets, but, in fact, big data is being used for more and more precise forms of discrimination - a form of data redlining.
We use nearly 5 thousand different data points about you to craft and target a message. The data points are not just a representative model of you. The data points are about you, specifically.
You can't talk about big data without talking about things like privacy and ownership.
Apple knows a lot of data. Facebook knows a lot of data. Amazon knows a lot of data. Microsoft used to, and still does with some people, but in the newer world, Microsoft knows less and less about me. Xbox still knows a lot about people who play games. But those are the big five, I guess.
The Industrial Revolution was about making physical things. Many of the manufactured goods that were once tangible objects have now been reduced to bits and bytes of data.
Big data knows and can deduce more about you than Big Brother ever could.
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