A Quote by Kate Crawford

The promoters of big data would like us to believe that behind the lines of code and vast databases lie objective and universal insights into patterns of human behavior, be it consumer spending, criminal or terrorist acts, healthy habits, or employee productivity. But many big-data evangelists avoid taking a hard look at the weaknesses.
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.
A great deal of creativity is about pattern recognition, and what you need to discern patterns is tons of data. Your mind collects that data by taking note of random details and anomalies easily seen every day: quirks and changes that, eventually, add up to insights.
While many big-data providers do their best to de-identify individuals from human-subject data sets, the risk of re-identification is very real.
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.
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.
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.
A data scientist is that unique blend of skills that can both unlock the insights of data and tell a fantastic story via the data.
Let's look at lending, where they're using big data for the credit side. And it's just credit data enhanced, by the way, which we do, too. It's nothing mystical. But they're very good at reducing the pain points. They can underwrite it quicker using - I'm just going to call it big data, for lack of a better term: "Why does it take two weeks? Why can't you do it in 15 minutes?"
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.
The ability to collect, analyze, triangulate and visualize vast amounts of data in real time is something the human race has never had before. This new set of tools, often referred by the lofty term 'Big Data,' has begun to emerge as a new approach to addressing some of the biggest challenges facing our planet.
One [Big Data] challenge is how we can understand and use big data when it comes in an unstructured format.
Biases and blind spots exist in big data as much as they do in individual perceptions and experiences. Yet there is a problematic belief that bigger data is always better data and that correlation is as good as causation.
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
There are a number of fascinating stories included in 'The Human Face of Big Data' that represent some of the most innovative applications of data that are shaping our future.
By using big data, it will also be possible to predict adverse weather conditions, rerouting ships to avoid delays, and monitor fuel data, thereby allowing companies to optimize their supply chains and the way they drive their business.
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