Deepnote
Collaborative data notebook for SQL and Python analytics; the API runs notebooks and returns execution status and project metadata.
- Category
- Cloud & Data Platforms
- Type
- Data science platform
- Interface
- REST API
- Built with
- Connect Any API
- Credentials
- API key
02Data
What you can sync.
- Notebook runs
- Execution status
- Projects
- Integrations
Put Deepnote notebook runs next to revenue and usage, so every cost has an owner and a reason.
Need more? Name any other Deepnote data the API returns, and the AI adds it to the connector.
03Credentials
Credentials you will need.
- An API key
Deepnote uses an API key. You add the credentials once, when the AI asks for them, and it tells you where to create them in Deepnote if you need help.
04How it works
How it works in DataMind.
-
Pick Deepnote.
Open Lake, pick Deepnote in the source picker and name the connection. Connect Any API opens with a ready prompt that points the AI at the Deepnote API docs.
-
Answer a few questions.
The AI reads the Deepnote documentation, then asks which credentials you will use, which data to sync (for example notebook runs and execution status), whether you want a one-time load or a recurring sync, and which accounts or filters apply.
-
Your data lands in Lake.
It builds the connector, tests it and shows you sample rows. Then Deepnote data loads into your Lake on your schedule, ready for the Warehouse, DataPrism BI and AI Minds.
