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The site is adjusted in a few milliseconds.Spotting helpful patterns when you are swimming in data is tough, explains Genevieve Graves, an astrophysicist turned data scientist.
Making use of big data is tough, while it's all essentially binary numbers at heart, the actual data can exist as numbers, words, pictures, sounds or movies, it's often unstructured, so it's hard to find the useful stuff and there is a lot of it to check.
But getting people to input data is tough.
"Small-business data is tough to come by, but point-of-payment experiences are very representative of how a small business conducts business," says Ida Wainschel, program director for Trade Exchange.
Reliable startup data is tough to find and track in Asia — let alone in the U.S. or other parts of the world — and, with the region an increasingly important one, this is a problem that Techlist, a service from fellow blog Tech In Asia (hi guys), aims to solve.
Food feedback comes at us from several directions and synthesizing the data is tough, especially when the cranberry sauce is winking from across the table.
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Health data, in particular, is tough to use because of legal (HIPAA) requirements that prohibit medical staff what they can share in writing.
But as he told Wired earlier this year, getting consistent data on consciousnesses is tough as consciousness shifts around with stimulus.
Companies pay for it because managing data traffic is tougher than mere computation.
Even data.gov's 'Internet Web Expert' James Hendler said, "Searching for data on the site is tough — keyword search is not a good way to look for data", and talked about efforts to use more metadata.
But without more concrete metrics to counter publicly available data, it's tough to drink that Kool-Aid.
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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