Data Engineering: SQL Transformer
We’ve introduced SQL Transformer as part of Tray Data Engineering capabilities - enabling you to run SQL queries against data loaded from files within your workflows.
Instead of building complex, multi-step data-shaping logic using loops, list helpers, and script steps, you can now use a single SQL query to join, filter, aggregate, and reshape datasets. This makes workflows easier to read, maintain, and scale.
What you can do
- Join data from multiple files
- Filter and transform large datasets in a single query
- Perform aggregations and grouping operations
- Reshape data before sending it to downstream systems or AI tools
Why it’s useful
- Reduce workflow step count and complexity
- Replace row-by-row processing with set-based logic
- Improve maintainability of data-heavy workflows
- Prepare structured data for AI, analytics, or external systems
If you can express the outcome in SQL, you can execute it in one step.
If you're interested in using SQL Transformer, please reach out to your Customer Success Manager or Account Executive to request access.
You can learn more in the documentation.