A Quote by Rick Smolan

Big Data is just that - big. But, it's a term that is largely misunderstood and difficult to explain. — © Rick Smolan
Big Data is just that - big. But, it's a term that is largely misunderstood and difficult to explain.
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?"
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.
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 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
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'm going to say something rather controversial. Big data, as people understand it today, is just a bigger version of small data. Fundamentally, what we're doing with data has not changed; there's just more of it.
One [Big Data] challenge is how we can understand and use big data when it comes in an unstructured format.
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.
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.
It's difficult to explain love. You want to explain water? You need a book for it. There are many different ways to explain what water is. Love is big, it's very big. I know that I have tons of it. But maybe we don't want to open up so much, and we think, maybe we don't have so much, but yes, you know that you have tons of love. We all do. Through that love we can connect, we can heal each other, we can make people, all of us, happy, joyful, and make a better world.
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.
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.
Too many poets write poems which are only difficult on the surface, difficult because the dramatic situation is easily misunderstood. It's not difficult to write poems that are misunderstood. A drunk, a three-year-old-they are easily misunderstood. What is difficult is being clear and mysterious at the same time. The dramatic situation needs to be as clear in a poem as it is in a piece of good journalism. The why is part of the mystery, but the who, what, where, and when should all be understood.
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.
I sit on the board of Cloudera, a big vantage point of big data.
We don't use the term 'big data' - not on our website, not with customers. Saying it sets up expectations, the wrong expectations.
This site uses cookies to ensure you get the best experience. More info...
Got it!