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The Large Hadron Collider in Cern, for example, produces 15 petabytes of data a year.
Over that time he has built up an archive of 12m images, and he currently produces about a terabyte of data a year.
Every record includes a caller's number, the number of the person called, the time of day, the duration of the call and so on, resulting in 18m gigabytes of billing data a year.
The problem is that a company will often not remember how to decrypt data a year or two after encrypting it.
It's estimated that the LHC will generate five to eight petabytes of data a year (enough to fill a stack of CD-ROMs between 8 and 13 kilometres high) and that those data will be used by 6000 scientists around the world.
Researchers estimate that Advanced LIGO will generate more than 1 petabyte of data a year, the equivalent of 13.3 years of high-definition video.
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Inside 'Dear Data,' A Year-Long Experiment in Visualizing Daily Life.
Inside 'Dear Data,' A Year-Long Experiment in Visualising Daily Life.
Intervals were explored for same-year data, a 1-year delay, and a 2-year delay between exposure and outcome.
Instead of just a little bit of narrow, crappy data once a year, we'll be harvesting crappy data every day.
And they want those companies to hold all that data for a year or more.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com