In an era where businesses must adapt to fast-paced environments, real-time automated decision-making has become a cornerstone of operational efficiency and competitive advantage. This capability involves a seamless blend of decision logic, cutting-edge infrastructure, robust data strategies, and precise application handling. Organizations striving for agility and responsiveness must master the art of designing systems that enable instant, data-driven decisions while ensuring consistency, accuracy, and scalability...
Yeah the addition of window functions onto sqlite last year was quite a good feature to enable more data use cases with sqlite.
The exclude clause is part of the "window" configuration which defines which row to process, with it you can for instance define a range between all the previous and next rows and check if your data-point looks abnormal.
"Colab is still a relatively closed environment; at one point, I wanted to add a Python package and couldn't" - quite a big drawback for a data-science tool. CoCalc seems interesting though.
There is no issue hiring juniors, they have a lot to learn and they should be coached through it for sure. That mid level, help coach juniors, is also not an issue. But I would rather hire a junior analyst or a junior engineer than a junior data-scientist. The breadth of what they need to learn before actually delivering value is quite vast.
I can hire an analyst or engineer and quickly they will be able to learn, get good at something and deliver value. After 2 years they can easily grow into a data-scientist with the good base they have had from their previous positions.
Some organization essentially rebrand analysts positions to "junior datascientist", but I believe this make it a mismatch of expectation for graduates getting out of school.
It's a job you grow into by not working at the job.: Agreed! There are quite a few paths which makes it easy to grow into, such as analyst or data/software engineer. There is however a mismatch of expectation that you can just start as a data-scientist out of school, which represent a steep learning curve and that people are usually not ready for.
Oh we disagree entirely. I am openly mocking the idea that you should learn the job by not doing it. That data scientists are just oh so special that no one can be a junior at it.
It's ridiculous. If you can't mentor someone at the job, then that speaks to your failures. It's not the job that's the problem.
You can have junior position for everything, so long as you revise your expectations.
A lot of firm, rebrand analysts jobs to be junior data-scientists position to essentially attract candidates, so yeah you can be "junior" at it, but it's essentially a different job.
