A Quote by Jay Baer
The future of marketing isn't big data, it's big understanding.
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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.
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 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
One [Big Data] challenge is how we can understand and use big data when it comes in an unstructured format.
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.
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.
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.
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.
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.
Big Data is neither color-blind nor gender-blind. We can see how it is used in marketing to segment people.
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?"
'Personalization' is a popular word in retail, and people often misuse it to describe simple marketing tactics, like segmenting emails or using big data to identify the likely gender of a visitor to their websites.
Every company has big data in its future and every company will eventually be in the data business.
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.
