> ## Documentation Index
> Fetch the complete documentation index at: https://docs.e6data.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Run your first query

> Run your first real query in e6data after setup - open the SQL Editor, pick a cluster and catalog, and confirm results.

Once your workspace is set up - a catalog connected and a cluster running - run a query to confirm everything works end to end.

## Run a query

1. Open the workspace's Compute Plane and go to the **SQL Editor**.
2. In the Query Action Bar, select your **catalog**, **database**, and **cluster**.
3. Enter a query and click **Run** (or press `Cmd/Ctrl + Enter`):

   ```sql theme={"theme":{"light":"github-light","dark":"github-dark"}}
   SHOW DATABASES;
   SELECT * FROM your_schema.your_table LIMIT 10;
   ```
4. Confirm results appear in the results pane below the editor.

> [!NOTE]
>
> If your cluster is suspended, the first query resumes it automatically.

If results return, your deployment is working: the cluster reached your catalog's metadata and read your data in place.

## If the query fails

* An access error usually means the engine can't read your storage - recheck the cloud access you granted during setup.
* A connection or schema error usually points to the catalog - re-open it and use **Test Connection**.
* A timeout may mean the cluster is under-provisioned or the query is heavy - see [Cluster sizing and scaling](https://docs.e6data.com/query/clusters/sizing-and-scaling.md).

## Where to next

* **Secure your workspace** - configure SSO, roles, and access control: [Identity and RBAC](https://docs.e6data.com/platform/identity.md).
* **Connect a BI tool** - point Tableau and other tools at your cluster: [BI tool recipes](https://docs.e6data.com/query/connect.md).

## Keep going across e6data

> **[Connect your tools](https://docs.e6data.com/query/connect.md)**
>
> Python, JDBC, PostgreSQL protocol, Tableau, Power BI and notebooks.

> **[Control who sees what](https://docs.e6data.com/query/governance.md)**
>
> Catalog access control, column masking and row filters.

> **[Add live data](https://docs.e6data.com/ingest.md)**
>
> Stream Kafka, CDC and HTTP data into Iceberg tables with Ingest Engine.


This documentation is built and hosted on [Mintlify](https://mintlify.com), a developer documentation platform.