Here is how to build a collaborative data analysis notebook with Deepnote.

Step 1: Create a project and notebook. Sign up at Deepnote and start a new notebook. Deepnote runs in the browser, so there is no local setup required.

Step 2: Connect your data. Connect to a database, warehouse, or upload a file. Use SQL cells to query tables and Python cells for deeper analysis, all in the same notebook.

Step 3: Collaborate in real time. Invite teammates to edit the notebook simultaneously. Comment on cells, discuss findings in context, and keep everyone on the same page.

Step 4: Use the built-in AI assistant. Ask the AI to write a query, explain a confusing output, or debug an error. It accelerates analysis and helps less experienced teammates learn.

Step 5: Publish a dashboard. Turn your notebook cells into a live, shareable dashboard or report. You can even schedule recurring runs to keep your analysis up to date.

Deepnote makes data projects faster and more transparent. For teams, combining Python, SQL, live collaboration, and AI in one notebook is a major productivity win.

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