DFS Pro
DFS Pro turns connected data into governed data assets and repeatable data workflows. Use it when operational data needs lifecycle control, stewardship, version history, fusion, review, audit, or BI reporting.
What users do in DFS Pro
| Task | UI area | Result |
|---|---|---|
| Create governed data assets | Dataset Center | A dataset exists with source type, schema, profile, owner, and lifecycle status. |
| Validate data assets | Dataset Detail | A stewarded dataset can be used downstream. |
| Review schema changes | Dataset versions and change impact | Downstream users understand what changed. |
| Build reusable processing logic | Method Library | A method can be tested, published, versioned, and used in fusion tasks. |
| Fuse multiple datasets | Data Fusion | Reviewed outputs combine records from multiple sources. |
| Resolve uncertainty | Review Queue | Conflicts, low-confidence results, source disagreements, and manual flags are reviewed. |
| Fix rejected rows | Rejected Rows | Upstream corrections can be tracked and reprocessed. |
| Track evidence | Audit Trail and Metrics | Changes, run outcomes, and operational health are traceable. |
| Build reports | DFS Pro BI | Reviewed datasets can drive dashboards and scheduled reports. |
Lite to Pro workflow
DFS Lite connector -> mapped and synced data -> DFS Pro dataset
-> method or fusion task -> review queue -> validated output
Move from DFS Lite to DFS Pro when a data feed needs any of the following:
- data steward;
- dataset lifecycle;
- schema versioning;
- profile and preview;
- lineage or change-impact review;
- multi-source fusion;
- review queue;
- BI reporting.
Recommended first path
- Create a connector in DFS Lite.
- Map and sync source data.
- Check data quality.
- Create a DFS Pro dataset from the connector output or imported data.
- Preview and profile the dataset.
- Assign a steward.
- Validate the dataset.
- Use it in a fusion task, AI Agent workflow, or BI report.
Read next
| Page | Use |
|---|---|
| Datasets | Create and validate governed datasets. |
| Fusion Tasks | Combine multiple datasets with reviewable matching logic. |
| Review Queue | Resolve conflicts, low-confidence outputs, source disagreements, and rejected rows. |