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Consider the data pouring into the algorithms.
Second, consider the data.
Consider the data on reading.
Consider the survey data.
Consider the recent data on employee disengagement.
We'll see data, insights, and analytics thread throughout the process.
Considering the generally significant agreement between the two approaches, we expect that array data will continue to be useful for generation of experimentally robust and enduring insights [82].
Considering the wide range of users we projected would engage with the app, we were interested to see if any data collected from the campaign might capture some insights into consumer behavior.
It gives users the ability to connect data, insights, and people across their entire organization.
Consider the value of data.
Number three: everyone talks about big data, but where is the big data insight and business insight that comes from that?
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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