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Shared Tutorials and Saved Queries

Find a tutorial​

In the SQL editor's sidebar, open the Saved tab and expand Shared with me. Shared tutorials appear there as one list, each with tags such as ai-ml. Type in the search box to filter: search matches a query's name, its SQL text, and its tags. Hover over a tutorial to see its author and tags.

The AI & ML tutorials are named Tutorial: …, for example Tutorial: Churn Prediction End-to-End; type tutorial to list them all. The Order Processing walkthrough isn't in the shared list; download its SQL and paste it into a new editor tab.

Run a demo safely​

  1. Select your Gnok connection and open a current shared tutorial.
  2. Read prerequisites, especially required providers, runtimes, grants, and model endpoints.
  3. Use a schema intended for tutorial fixtures. Reset statements can replace existing objects with the same names.
  4. Run the statements in order, then compare each result with the walkthrough.
  5. Use Save As… if you want to keep an adapted version.

Sharing a tutorial distributes its SQL template. It does not share another tenant's data, models, credentials, or permissions. Native examples, external AI calls, and scheduled workloads have different prerequisites; start with tutorial setup.

Keep personal and shared work organized​

Save SQL with a descriptive name and use folders to organize your own library. Folders are personal: they organize your saved queries, not what others see under Shared with me. Add tags when you share a query so others can find it by searching.

Review the sharing audience before saving. SQL can contain private table names, comments, or literal values. Share only material appropriate for that audience, and keep credentials out of SQL text.

Load an updated tutorial​

Studio preserves drafts. Refreshing the browser may reopen an older version. Save changes you need, close the old editor tab, and reopen the tutorial from Shared with me, or download its current SQL into a fresh tab.

Browse the AI & ML tutorials and Procedural SQL example for model explanations and expected outputs.

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