A Quote by Charles Babbage
Errors using inadequate data are much less than those using no data at all.
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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?"
The data set of proxies of past climate used in Mann...for the estimation of temperature from 1400 to 1980 contains collation errors, unjustifiable truncation or extrapolation of source data, obsolete data, geographical location errors, incorrect calculation of principal components and other quality control defects.
When dealing with data, scientists have often struggled to account for the risks and harms using it might inflict. One primary concern has been privacy - the disclosure of sensitive data about individuals, either directly to the public or indirectly from anonymised data sets through computational processes of re-identification.
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.
As a Facebook user, do I have control of the data Facebook keeps about me? Concretely: can I examine and modify that data using tools of my choosing which are built for my needs?
Today, I think a CFO needs to be more of an operating CFO: someone who's using the financial data and the data of the company to help drive strategy, the allocation of capital, and the management of risks.
We are ... led to a somewhat vague distinction between what we may call "hard" data and "soft" data. This distinction is a matter of degree, and must not be pressed; but if not taken too seriously it may help to make the situation clear. I mean by "hard" data those which resist the solvent influence of critical reflection, and by "soft" data those which, under the operation of this process, become to our minds more or less doubtful.
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.
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.
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.
This is going to sound cheesy, but with acting there are so many tools. When you're on camera, you're using all of it. You're using the voice, you're using your body, you're using wardrobe, all of it, but it's funny, once you take all of those things away, you realize how much you rely on the physicality.
They're trying to put data centers in cold environments because they're actually generating so much heat now; they're using up so much electricity.
The first wave of the Internet was really about data transport. And we didn't worry much about how much power we were consuming, how much cooling requirements were needed in the data centers, how big the data center is in terms of real estate. Those were almost afterthoughts.
In the past, Google has used teams of humans to 'read' its street address images - in essence, to render images into actionable data. But using neural network technology, the company has trained computers to extract that data automatically - and with a level of accuracy that meets or beats human operators.
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.
In my view, our approach to global warming exemplifies everything that is wrong with our approach to the environment. We are basing our decisions on speculation, not evidence. Proponents are pressing their views with more PR than scientific data. Indeed, we have allowed the whole issue to be politicized-red vs blue, Republican vs Democrat. This is in my view absurd. Data aren't political. Data are data. Politics leads you in the direction of a belief. Data, if you follow them, lead you to truth.
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