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Einblick reimagines the modern data science workflow in a collaborative data science canvas, rather than a linear notebook. Working in a canvas environment offers many advantages including live collaboration, an expansive visual interface, and a progressive computation engine. In this article, we’ll highlight one of the key ways we’re saving data scientists time–our operators. We’ll go through a couple of our core operators, why Python is such a crucial part of our software solution, and how we augmented our offerings with a user operator interface. The latter allows users to customize and use their own operators, which can be used in any Einblick canvas, and shared with other Einblick users.