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The quantity of business data doubles every 1.2 years, by one estimate.
Therefore, this study made use of more than double the quantity of data generated for marker discovery than was used for lupin.
It does not offer an interpretation of this immense quantity of data.
One growing difference concerns the quantity of data coming from government departments and other bodies.
But crucial to machine learning is a huge quantity of data.
As a result, the quantity of data available varies.
In fact, it's the quantity of data out there that makes finding the right details especially difficult.
Why? Insufficient quality and quantity of data.
No other vertical has that quantity of data.
The sheer quantity of data exceeds the capacity for analyzing that data in many organizations.
The bigger the quantity of data, the more time it takes to run the tests.
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CEO of Professional Science Editing for Scientists @ prosciediting.com