By Jakub on January 31, 2022
There used to be a time when the biggest bottleneck for solving the hardest problems in data science was access to more compute power. However, as we moved towards more complex problems, we realized that more compute wasn’t enough. The biggest bottleneck was actually something much more subtle. It was the way how data scientists and domain experts communicated. How they exchanged ideas. How they asked for feedback. We realized that the biggest bottleneck wasn’t the performance of the tools, but the tools themselves. We realized that a new kind of tool would have to be invented.
Notebooks represent a new kind of computational platform. An interactive document, powerful enough to solve the most difficult problems, yet at the same time, collaborative enough to effectively communicate your findings with others. The best data science notebook would promote reproducibility, version control, and collaboration with your team. That’s the kind of notebook we decided to build.
As data scientists, analysts, and engineers, we often struggled to bring the results of our work into the hands of decision makers. The feedback cycles were long, and key stakeholders were left out. We were using state of the art tools and state of the art processes, but our tools were failing us. They were built for engineers, not for data scientists.
We started Deepnote at the beginning of 2019. Supported by top investors, we set out to build a new kind of data science notebook. Building on top of Jupyter’s pioneering ideas, we combined our experiences from Two Sigma, Palantir, Mozilla, and Google, to take notebooks to a new stage in their evolution.
Today we are excited to announce our $20M Series A funding round with a group of world-class investors, all doubling down on that vision.
As data scientists and analysts, we are not working alone. In fact, we love to share our work with others. That’s because data science is fundamentally collaborative. We aren’t solving our own problems, we are solving the organization's problems. And those solutions need to be shared.
Ever since our public release, we’ve started to see something truly magical. Not only were data scientists enabled to do their best work, they were discovering a brand new way of working with data. A new standard was emerging and hundreds of thousands of data scientists decided to get on board. Deepnote transformed how organizations operate. Deepnote changed how newcomers get introduced into the field. Deepnote became the standard for the new generation of data scientists.
We envision a notebook that helps everyone work with data. A place where teams can collaborate without barriers. A place where problems get solved. As we lower the barriers to entry, more people will be able to participate in data exploration. At the end of the day, we are all explorers.
To get there we’ll be looking for more great makers and doers to join our team. Throughout history, it took the brightest minds of the generation to build a new kind of medium. That’s the team we are building at Deepnote. Join us.
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