Deepnote, an early-stage startup backed by Accel and Index Ventures, launched version 1.0, opening up to the general availability of collaborative data science notebooks to data teams. Data team efficacy relies on the process of access to, exploration of, and collaboration around data—for example, when an organization needs to make a data-informed decision, it will rely on data teams to explore datasets and share insights that lead to action. This process is siloed within a single department, findings are inconsistent, and insights quickly become out of date. Deepnote makes data collaboration a reality improving three pain points of traditional data science notebooks:

  1. Collaboration: Sharing analysis and collaboration is as easy as sending a link because everything is hosted in a fully-managed cloud environment. Analysis is done in real-time with multiplayer mode if needed. And everything is organized and hosted in a single place.
  2. Connectivity: With dozens of native integrations to tools in the modern data stack—Snowflake, BigQuery, Postgres, S3, GitHub—data teams can seamlessly connect to the tools they’re already using.
  3. Productivity: Underserved data analysts and scientists are now equipped with productivity features—reproducibility, autocomplete, scheduling, version control—to do better work in less time.