"We're working in uncharted territory and our work is highly R&D focused. Machine learning is a very empirical discipline, so iteration speed is everything. Working in Deepnote is like code review and rapid prototyping at the same time, saving valuable time in the iteration cycles. But as opposed to code …

"Since metrics require a lot of input from subject matter experts, data consumers, and business stakeholders to define and align on definitions, we needed a collaborative layer where we could get immediate feedback."

"Collaborative data analysis where team members can freely share their work and get feedback. This made the analysis workflow much faster."

"I just love how SQL is now a first-class citizen in Deepnote notebooks! It is SO easy to query databases!"