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Webinar Recap: Data Science 2.0 and Scaling Distributed Teams

Posted by Tyler Whitehouse on Jun 30, 2020 3:09:15 PM

We did our first webinar on June 23, 2020, and we wanted to follow up with a brief post recapping the topics covered and giving access to a recording of the webinar.

In the webinar, Tyler Whitehouse (CEO) and Dean Kleissas (CTO) presented some slides and gave a product demo. The intent was to explain a bit about why decentralization is the best way to scale collaboration and productivity for teams on hybrid and multi-cloud environments.   

Broadly speaking, decentralization is the attempt to enable data scientists to work across a variety of devices and resources in a self-service fashion. It is a flexible approach that, if done properly, can eliminate the cost and practical problems of centralized approaches. The problem is that decentralization requires a lot of technical skill and diligence.

We have found that the key to scaling a decentralized approach is to provide lot of automation at the local level, not just in a managed cloud. Local automation drastically reduces the skill burden and the amount of time required to make decentralized approaches feasible. 

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Topics: Data Science, Containers, Git, Jupyter, RStudio