Sentence examples for nebulous data from inspiring English sources

Exact(2)

"It resulted in that nebulous data zone that we were so fearful about," Borio says.

This article tackles two areas linked by the 'species concept' problem: the ideal of a universally applicable measure of biodiversity across all Domains of life, and a standardised and inclusive way of dealing with the nebulous data from metagenomic surveys.

Similar(58)

The move to offer Vedo points to another big trend we've been seeing in enterprise: the larger push to harness and shape the nebulous "big data" promise.

Unfortunately, the definition of stem cells remains to be nebulous and data can be contradictory.

While you might assume, by hearing AI and video in the same sentence, that what we have here is a solution that somehow uses computer vision, in fact Conviva relies on the machine learning aspect of that nebulous area of data science.

Financial types are likely still spooked by the nebulous idea of posting their data on the Internet and storing it in "the clouds," but SDC is enough to allay most of those fears.

That's critical when building towards a big but nebulous vision of a world where our data is always at our fingertips.

However, Cox feels that "conclusions derived from the frequentist approach are more immediately secure than those derived from most Bayesian analysis" because [prior] "information is typically more fragile or even nebulous as compared with that typically derived more directly from the data under analysis".

Your toaster is hackable, yes (as may be the rest of these smoking guns in your city), but at the same time, in a nebulous trade-off, with "dictators dying off and the data trail of bad behaviour growing, the biggest dirty networks are on the brink of collapse".

Data saturation of course is a sometimes nebulous concept in the work of qualitative researchers as there are few clear guidelines beyond individual researcher experience and judgment for establishing when saturation has been achieved [ 40, 41].

Unfortunately for data-driven executives, the answer is more nebulous than just getting better percentages out of recruiting and hiring programs.

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