A Quote by David McCandless

Data is the new oil? No: Data is the new soil. — © David McCandless
Data is the new oil? No: Data is the new soil.
We all say data is the next white oil. [Owning the oil field is not as important as owning the refinery because what will make the big money is in refining the oil. Same goes with data, and making sure you extract the real value out of the data.]
Data is the new soil, because for me, it feels like a fertile, creative medium. Over the years, online, we've laid down a huge amount of information and data, and we irrigate it with networks and connectivity, and it's been worked and tilled by unpaid workers and governments.
Data is the new oil.
People are saying, 'Big Data is the new oil.'
Data is the new science. Big Data holds the answers. Are you asking the right questions?
We need a new generation of executives who understand how to manage and lead through data. And we also need a new generation of employees who are able to help us organize and structure our businesses around that data.
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.
You have to imagine a world in which there's this abundance of data, with all of these connected devices generating tons and tons of data. And you're able to reason over the data with new computer science and make your product and service better. What does your business look like then? That's the question every CEO should be asking.
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.
Evolving technologies that allow economists to gather new types of data and to manipulate millions of data points are just one factor among several that are likely to transform the field in coming years.
Everything is changing now that we are in the cloud in terms of sharing our data, understanding our data using new techniques like machine learning.
I think audiences ultimately want something new. I think the business model for a franchise is such that it's very low risk because you have data and studios love data.
The biggest mistake is an over-reliance on data. Managers will say if there are no data they can take no action. However, data only exist about the past. By the time data become conclusive, it is too late to take actions based on those conclusions.
I tend to write poetry that is rich in data of various sorts. The lyric poem isn't perfectly suited to accommodating such data, so I've had to find new ways to say everything that I want to say.
A scientist naturally and inevitably ... mulls over the data and guesses at a solution. He proceeds to testing of the guess by new data-predicting the consequences of the guess and then dispassionately inquiring whether or not the predictions are verified.
One of the myths about the Internet of Things is that companies have all the data they need, but their real challenge is making sense of it. In reality, the cost of collecting some kinds of data remains too high, the quality of the data isn't always good enough, and it remains difficult to integrate multiple data sources.
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