What are Data Transforms in Data Cloud and when do you use them?

Data Transforms are SQL-based transformation jobs that read from existing DMOs, apply logic, and write the results to new derived DMOs. They are analogous to SQL views or materialized views within Data Cloud. Use cases:

1. Cleansing and standardizing raw ingested data (e.g., normalizing phone number formats).
2. Joining data from multiple DMOs into a single denormalized table for easier segmentation.
3. Creating derived metrics or categorizations that don't fit the standard Calculated Insights framework.
4. Preparing data for activation targets that require a specific schema. Scheduled Refresh — Data Transforms can be set to run on a schedule (hourly, daily); the output DMO is updated on each run. This is distinct from Calculated Insights (metric aggregations) — Transforms produce new record-level DMOs rather than aggregated scores.