A Quote by Ben Bernanke

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.
We use nearly 5 thousand different data points about you to craft and target a message. The data points are not just a representative model of you. The data points are about you, specifically.
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?"
To make a vehicle autonomous, you need to gather massive streams of data from loads of sensors and cameras and process that data on the fly so that the car can 'see' what's around it.
Part of my responsibility as an officer was to oversee a team of analysts charged with synthesizing all of the data points on the map to see how one related to another. By bringing those data points together, a broader picture could be drawn and a strategy developed to counter the existing threat.
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.
Go out and collect data and, instead of having the answer, just look at the data and see if the data tells you anything. When we're allowed to do this with companies, it's almost magical.
Tape with LTFS has several advantages over the other external storage devices it would typically be compared to. First, tape has been designed from Day 1 to be an offline device and to sit on a shelf. An LTFS-formatted LTO-6 tape can store 2.5 TB of uncompressed data and almost 6 TB with compression. That means many data centers could fit their entire data set into a small FedEx box. With LTFS the sending and receiving data centers no longer need to be running the same application to access the data on the tape.
Computer science only indicates the retrospective omnipotence of our technologies. In other words, an infinite capacity to process data (but only data -- i.e. the already given) and in no sense a new vision. With that science, we are entering an era of exhaustivity, which is also an era of exhaustion.
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.]
Your body is spewing off millions of data points a second.
I am a data hound and so I usually end up working on whatever things I can find good data on. The rise of Internet commerce completely altered the amount of information you could gather on company behavior so I naturally drifted toward it.
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 think it's pretty obvious to most people that Napster is not media specific, but I could see a system like Napster evolving into something that allows users to locate and retrieve different types of data other than just MP3s or audio files.
We are now at a point in time when the ability to receive, utilize, store, transform and transmit data - the lowest cognitive form - has expanded literally beyond comprehension. Understanding and wisdom are largely forgotten as we struggle under an avalanche of data and information.
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.
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.
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