Data quality: the metrics to track on every import
5 min
Data quality cannot be judged by eye. Five metrics are enough to know whether a file can go into a database or needs another cleaning pass.
Five metrics to measure
Each metric maps to a check you can automate.
- Completeness: share of empty cells in mandatory columns.
- Uniqueness: number of strict duplicates and repeated keys.
- Validity: values matching the expected type (email, date, amount, postcode).
- Consistency: the same format convention across a whole column.
- Format accuracy: leading zeros, scientific notation, barcodes preserved.
From diagnosis to correction
Measuring only helps if fixing follows. Import Cleaner shows the number of issues per type, then lets you fix them in bulk or row by row, with global rules per column.
The dashboard keeps the history of your cleaned files and the number of fixed errors, so you can track the quality of a source system's exports over time.
Make the check systematic
When files always come from the same tool, save a mapping template: columns are recognised on every import and the same checks apply with no reconfiguration.
FAQ
- How many checks are applied?
- 26 automatic checks, including 5 dedicated to custom formats and local conventions.
- Can I track quality over time?
- Yes, the dashboard keeps the history of cleaned files and fixed errors on your device.
Measure your file's quality
A full diagnosis in one pass, then guided fixing.
Analyse my file