Sounds like the author wants to work at a university.
And that is probably where the best data science results are going to come from. Where inter-disciplinary teams and cross talk are the norm.
Science takes time to make sense of data.
We have figured out how to produce gigantic quantities of data, but that doesn't mean science gets faster.
Whether it is CERN or Wall Street or the NSA or Facebook processing the data takes it own sweet time.
And when they don't find anything or use it in misguided ways it takes time to work that out too. Because everyone is conditioned to hide that.
It took 20-30 years before anyone seriously took the experiments (data) of a Micheal Faraday to get an accurate math model of electromagnetism. There were a whole lot of famous mathematicians around, and all of them had access to the data. So why did it take time?
Orgs with data don't have that kind of time. And the truth is these mythical generalists don't exist. They really can't be quickly mass produced like vegetables. And on top of it all orgs and execs are conditioned to not share their data.
This combo of factors is why we see so many bad consequences and erosion of trust in every single org dealing with big data.
We are all living under the delusion that Data Science is like working on crude oil at a refinery. It's more like working at a landfill with arbitrary deadlines to find diamonds skewing incentives for the data to be misused.
And that is probably where the best data science results are going to come from. Where inter-disciplinary teams and cross talk are the norm.
Science takes time to make sense of data.
We have figured out how to produce gigantic quantities of data, but that doesn't mean science gets faster.
Whether it is CERN or Wall Street or the NSA or Facebook processing the data takes it own sweet time.
And when they don't find anything or use it in misguided ways it takes time to work that out too. Because everyone is conditioned to hide that.
It took 20-30 years before anyone seriously took the experiments (data) of a Micheal Faraday to get an accurate math model of electromagnetism. There were a whole lot of famous mathematicians around, and all of them had access to the data. So why did it take time?
Orgs with data don't have that kind of time. And the truth is these mythical generalists don't exist. They really can't be quickly mass produced like vegetables. And on top of it all orgs and execs are conditioned to not share their data.
This combo of factors is why we see so many bad consequences and erosion of trust in every single org dealing with big data.
We are all living under the delusion that Data Science is like working on crude oil at a refinery. It's more like working at a landfill with arbitrary deadlines to find diamonds skewing incentives for the data to be misused.