Most data scientists know git! Or, at the very least, how to follow a step-by-step git guide.
If notebooks are tracked anywhere at an org it's either where their code is stored (GitHub/GitLab), or in their managed notebook environment (Databricks/Hex)
It's a mix of things, but the big one was ROS bag files for robots. So a lot of the conventional up-to-the-minute metrics workflows oriented around grafana/kibana don't really pan out when you're very interested in a five minute window that occurred three days ago, buried in a 1gb datafile.
If notebooks are tracked anywhere at an org it's either where their code is stored (GitHub/GitLab), or in their managed notebook environment (Databricks/Hex)
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