Notebooks and Dashboards

Notebooks

Open Notebooks to combine SQL, Python, and explanatory content. Select the intended execution context before running cells. Where Python notebook execution is enabled, the pre-installed gnok helper connects with the notebook's authenticated context:

import gnok

gnok.sql("SELECT 1 AS connected")

Run cells in dependency order and inspect their outputs. Variables in a live Python session are not a substitute for saved data; restarting a kernel requires rerunning setup cells.

The Python notebook guide documents data access, model registration, and inference helpers. Supported packages and compute capabilities are determined by the hosted notebook environment.

Scheduled notebooks

Scheduled runs need an authorized execution identity, accessible inputs, and a configured notebook runner. Review the schedule's run history and outputs. A saved schedule alone does not prove that a run completed, and interactive access does not automatically grant background execution access.

Dashboards

Open Dashboards to assemble and revisit visual views of query results. Check the underlying query, filters, connection, and permissions when a chart is empty or unexpected. Validate totals against the source query before using a chart for business decisions.

Dashboard sharing is separate from saved SQL sharing. Inspect the audience and any link-sharing controls before distributing a dashboard; links and visual outputs can expose data beyond the people who edit the source query.

Choose the right tool

Use a worksheet to develop SQL, a notebook for analysis with code and narrative, and a dashboard for a repeatable visual view. Keep source queries and assumptions understandable so another authorized user can reproduce the result.