Data Quality
Senzo applies a series of validation checks before writing any data to the database. Understanding these checks helps you prepare clean files and troubleshoot issues quickly.Validation layers
Data goes through three validation layers during upload:- Structural validation — file can be parsed, headers detected, encoding correct
- Field validation — required fields present, values in expected formats
- Business validation — values make operational sense, no conflicts with existing data
Required field checks
Rows failing required field checks are rejected. The upload cannot complete if required fields are missing.
Format checks
Fields failing format checks generate warnings in the Review stage but do not block the upload. Review and confirm before proceeding.
Matching checks
Unrecognized names are flagged for resolution — you can add them to Settings or map them to an existing name.
Duplicate detection
Senzo detects duplicate rows — multiple rows with the same date, unit, and provider type combination. Duplicates are flagged in the Review stage. You must deduplicate before proceeding.Overlap detection
When uploading data for periods that already exist in the system, Senzo detects the overlap and presents options: Update, Skip, or Cancel. See Upload History for details.Best practices for clean data
Before exporting from your source system:- Confirm unit and provider type names match your Senzo Settings exactly
- Remove any summary, total, or blank rows
- Ensure all date fields are consistently formatted
- Exclude agency staff from headcount — track their hours separately in
agency_hours
- Open the file and do a quick visual scan for obvious issues
- Check the date range looks correct
- Verify row count is approximately what you expect
- Check the imported row count in the Review stage matches your expectation
- Navigate to Data Explorer after upload to verify data appears correctly
- Run Pulse Intelligence to confirm the new data generates expected insights