16 Deepnote Testimonials

"Great tool for those who work or want to work with data science."

"We are happy with Deepnote because it is a deeply technical and powerful tool that is also extremely accessible and intuitive. The data platform team has built an area where people can not just do great work, but share great work. Deepnote isn’t just accessible by experienced data scientists, it’s a tool where business analysts can do exploratory work and quickly migrate their ideas to production-grade systems and processes."

"Delightful user experience reminds me of Superhuman with the command palette and constant reminders of how to use hotkeys to work more efficiently."

"I have been trying out Deepnote for running shared Jupyter notebooks, and I’m very impressed by how smooth and powerful the whole experience is."

"Notebooks are often used as a quick prototyping tool, but we don't want to create one-off work. We want to invest in ideas that compound over time. Deepnote gives our team one place to create, store ideas, and build on top of the work of others. Visibility goes up over time."

"Our team was used to Google Docs, so when we moved over to Deepnote, we appreciated the similar look and feel as well as the added scalability — we’re no longer copying and pasting screenshots from external sources."

"Deepnote was incredibly easy to set up and allows us to start new notebooks in seconds. Working together with Deepnote gives us a great window into the ways candidates approach the interview problem."

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

"I knew I’d made the right decision when I started getting feedback from data scientists about how delightful their user experience was."

"Interactive plotting, directly connected data sets, zero-latency environment setup, and clever input widgets bridge the gap between a no-code GUI app for non-coders and a full-fledged programming environment for our engineers. More and more, the VantAI team is able to move discussions around abstract ideas and complex data out of presentation tools (e.g., PowerPoint) and into direct implementations in code."

"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 review via GitHub, you have direct access to the runtime and program state, which makes understanding complex models much easier and leads to much more spontaneous creative ideas."

"I enjoy writing code on weekends (mostly hack around with data analysis & machine learning in Python). This year I moved my dev environment fully to Deepnote, and I’m never going back. The future of coding is browser-based."

"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."

"It's sped up our testing and staging immensely. Deepnote feels more or less like developing locally on your computer, but since it's in the cloud and hosted, it's typically a step closer to being demoed and “shown off” than it would be if it were just local."

"I was personally skeptical about the 
performance of a collaborative, hosted platform, but when I used Deepnote to collaborate with a colleague and we were able to remotely troubleshoot and try different plots, I immediately saw its value."