All insights
Batch analysis
From individual images to structured batch analysis
Batch work is a different problem: the unit of attention becomes the record set, not the image.
Schema before summary
Batch analysis begins with agreement on what a record is. A required set of fields — an identifier, a sample reference, a status and a capture time — makes validation possible and makes every later summary meaningful.
Summaries should be derived, never stored
Totals, status distributions and failure counts should be calculated from the records currently loaded. A figure that outlives its data quickly becomes a figure nobody can reproduce.
- Compute totals from the loaded record set
- Report failure reasons as counts, not as narratives
- Export exactly the records shown after filtering
Partial success is normal
Real files arrive with malformed rows. A batch workflow that reports invalid records individually, while still presenting the valid ones, keeps the work moving without hiding the problems.