Another point in its favor is that more and more companies are using web technologies with a Node-based stack to build their products. If a data scientist is going to work closely with the product developers then speaking a common language is definitely an asset.
Better yet, the fact that everyone is working with the same technology means that integration with other products and services is easier, requiring less overhead and preparation. Just like how it is easier to communicate with someone when everyone speaks the same language.
New Tools for Data Science
Another fine example is TensorflowJS. For those who don’t know, Tensorflow is one of the most popular Machine Learning libraries out there. With its JS variant, you can run machine learning algorithms directly in your browser and/or on a Node.js server.
But why would you want to do that? Yes, a browser environment isn’t the most optimized workspace. But, on the other hand, it’s very convenient for quick prototypes, small projects, and apps that don’t require a lot of memory. Why create a virtual environment when a simple browser will do just fine?
The fact that we are getting these tools for the language that powers the internet and web applications, in general, is opening the door to new possibilities. With browser-based data science, we can play with new ways to process and present data in a friendly environment.
Another Tool in The Toolbox