A Quote by Margaret Heffernan
Big data will never give you big ideas... Big data doesn't facilitate big leaps of the imagination. It will never conjure up a PC revolution or any kind of paradigm shift. And while it might tell you what to aim for, it can't tell you how to get there
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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 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.
I'm not a big believer in revolutions. What people call revolutions in technology were more of a shift in perception - from big machines to PC's (the technology just evolved, fairly slowly at that), and from PC's to the internet. The next "revolution" is going to be the same thing - not about the technology itself being revolutionary, but a shift in how you look at it and how you use it.
One [Big Data] challenge is how we can understand and use big data when it comes in an unstructured format.
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.
You are what you think. So just think big, believe big, act big, work big, give big, forgive big, laugh big, love big and live big.
I will personally never ever get over the communal experience of theatrical cinema. I will never get over the scale of a big screen in relation to your small body, big sounds in a big room with a bunch of other people.
Big data has been used by human beings for a long time - just in bricks-and-mortar applications. Insurance and standardized tests are both examples of big data from before the Internet.
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.
The paradigm shift of the ImageNet thinking is that while a lot of people are paying attention to models, let's pay attention to data. Data will redefine how we think about models.
As we move into an era in which personal devices are seen as proxies for public needs, we run the risk that already-existing inequities will be further entrenched. Thus, with every big data set, we need to ask which people are excluded. Which places are less visible? What happens if you live in the shadow of big data sets?
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.
Most companies aim to get bigger. But beyond a certain point, bigness becomes synonymous with badness. Think of Big Pharma, Big Auto, Big Oil. Worse, if you are regularly described as one of the Big Four, Five, or Six in any business sector, you are probably already in the sights of regulators and lawmakers.
Bad language or abuse, I never, never use, Whatever the emergency; Though 'Bother it' I may Occasionally say, I never use a big, big D : What, never? : No, never! : What never? : Well, hardly ever! : Hardly ever swears a big, big D Then give three cheers, and one cheer more, For the well-bred Captain of the Pinafore!
Since my father's death, a lot of people have made it clear that they're not ready to give up the music. For me, it's a big, fat gift. I get to sing with a big orchestra and get to sing orchestrations that will never be old.
Some people try to tell me that science will never answer the big questions we have in life. To them I say: baloney! The real problem is your questions aren't big enough.
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