Data Generation
Generation Workflow
From schema parsing to generated rows and downloadable files.
Data Generation Workflow
This guide covers the complete user-facing flow for generating realistic records.
Input Sources
- Pasted schema text
- Uploaded schema files
- Migration-style SQL structures
Parse Stage
After submission, your schema is parsed into tables, fields, and indexes.
What Gets Detected
- Table names
- Column types and nullability
- Primary keys
- Foreign keys and references
Relationship-Aware Generation
Faker Forge respects table relationships so child rows reference valid parent rows.
Typical Order
- Parent tables generate first.
- Child tables generate after parent IDs exist.
- Self-referencing values are resolved during row generation.
Running Generation
Set table counts and mappings, then start generation from the configuration step.
During Execution
- Progress updates are emitted in real time.
- Partial output is streamed into generation files.
- Failures return an actionable error state.
Completion
When generation completes, output is available for edit and export flows.
Best Practices
- Start with smaller row counts to validate mappings.
- Confirm foreign key pairs before large runs.
- Keep high-cardinality text fields constrained where useful.