– by Gabor on September 15, 2022
Why we elevated text editing from an afterthought to a first class citizen in Deepnote notebooks.
– by Lukas on August 11, 2022
With Deepnote’s Microsoft SQL Server integration, data teams can efficiently query, extract, analyze, and model data stored in Microsoft SQL Server databases—all within the comfort of their notebook environment.
– by Elizabeth on July 28, 2022
A story of SQL-first notebooks, Deepnote—now a Snowflake Select Technology partner—and how Deepnote and Snowflake work together to power your SQL + Python workflows.
– by Harry on July 7, 2022
In this post, we’ll walk you through building and training a machine learning model in Deepnote and how to deploy it to Snowflake using Modelbit.
– by Lukas on June 30, 2022
With Deepnote and ClickHouse, data teams can efficiently query very large datasets, extract relevant data, and start analyzing and modeling data—all within the comfort of their notebook environment.
– by Allan on June 14, 2022
What makes Snowpark such a valuable asset for data science workflows, and how you can use its superpowers in Deepnote—Snowpark’s Python-ready partner
– by Jakub on May 26, 2022
We’re removing the “beta” label and making Deepnote generally available for the world’s best data teams.
– by Filip on April 14, 2022
We are excited to present Deepnote workspaces, a collaborative space for data teams of all sizes. A workspace is your data home and it helps you effectively organize and surface data projects, notebooks, and apps in one place, growing with you as your team and knowledge scales.
– by Allan on February 15, 2022
It's almost a given that the brightest tools in machine learning are written for Python. However, those with the deepest understanding of company data often speak SQL. Imagine what they could do if machine learning was at their fingertips—not in a Python environment but in the data layer—where they're most effective.
– by Simon on March 7, 2022
How we set up just-in-time profiling of our nodejs app when its event loop gets stuck.
By Jakub on January 31, 2022
Deepnote is quickly becoming a new standard for working with data. Today, we are announcing a $20M Series A led by Accel and Index. So why are the world’s best VCs doubling down on our vision? Because we are building a new kind of data science notebook.
– by Allan on January 6, 2022
Chances are you've experienced the initial excitement of learning something new followed quickly by a stark realization — you are not familiar with the prerequisites. You've actually got a mountain to climb! This article uses Great Expectations to highlight how Deepnote naturally lends itself to effective, context-based learning.
– by Elizabeth on December 31, 2021
It’s the last day of the year! Here’s a recap of how the Deepnote team, community and product evolved in 2021. We wish you happy holidays, and a great start to 2022!
– by Robert on November 29, 2021
Drive your product-led growth from Notion, and use Deepnote to keep your CRM up to date. Add new entries to your database, and enrich the existing ones using scheduled notebooks.
– by Elizabeth on November 2, 2021
How to build charts over Notion databases and keep your analytics & storytelling all in one place
– by Elizabeth on September 1, 2021
Throughout September 2021, you can find Deepnote on one of New York's biggest screens - the NASDAQ Tower in Times Square as a part of the Webex App Hub campaign.
By Jakub on June 15, 2021
Today, we’re launching Deepnote for Teams. And going forward, we will be building even more features that allow anyone in any organization (not just data scientists) to have a seat at the table.
By Jan on May 4, 2021
We looked at a couple of popular notebook platforms and compared their storage solutions both in managed and on-premise versions.
– by Filip on February 25, 2021
How to build a design system at a fast-moving startup and still leverage all the benefits a design system offers.
By Jakub on February 6, 2020
We’ve been working behind the scenes for the past year. Today, we’re excited to announce that we raised $3.8M from YC, Index and Accel to build a new kind of data science notebook. Here’s our story.
No credit card required. Run your first notebook in seconds.