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Notebooks bring exploratory analysis and operational diagnostics into Planasonix so you can prototype transforms, validate assumptions, and document findings next to the pipelines that productionize the work.

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Enterprise feature

Hosted notebooks with workspace credentials and pipeline integration require an Enterprise subscription. Other tiers may allow export-only workflows or local Jupyter without in-product execution—check your navigation and Plans and pricing.

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Jupyter-style notebooks

Planasonix notebooks support familiar cells (code, markdown), kernel selection, and variable inspection. You connect to approved warehouse or Spark clusters using connections admins provision—no personal passwords embedded in notebook JSON.
Profile samples, chart distributions, and test join logic before you commit nodes on the canvas.

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Pipeline integration

Notebooks can reference pipeline parameters and run context when your deployment wires them together. Typical patterns:
  • Read the same parameters a nightly job uses to filter partitions during investigation
  • Query staging tables a pipeline just wrote without copying connection strings manually
Notebook outputs may contain PII from production samples—apply masking cells and clearance rules consistent with your data classification policy.

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Next steps

Getting started

Create and run your first notebook.

Spark integration

Use Spark and Databricks compute.