Bulk data import and export
Bulk data moves employee information between KAMI and a spreadsheet. Use it to load people in at setup, to make wide changes, and to get data out for another system.
Where: My Team › Settings › Data & bulk tools › Bulk Data You need: the import/export employee details right
Import, or Profile Manager?
Both change many employees at once, and picking the wrong one wastes an afternoon.
- Bulk import suits adding people and large, structured changes — a new intake,
or a field applied across hundreds of records from a file you already have.
- Profile Manager suits editing people who already exist, in a
grid, where you can see what you are changing as you change it.
If you are correcting a handful of values, Profile Manager is faster and much easier to check. If you are loading a spreadsheet somebody else produced, import.
Export first, always
Before any import, export the current data. This gives you two things:
- The correct column layout, rather than a guess at what KAMI expects.
- A copy of what things looked like before — which is what you will want if the
import does something unexpected.
Editing an export is also less error-prone than building a file from scratch, because the identifiers already match.
Before you import
- Check your organisation structure exists. Employees reference
branches, departments and positions. If those are missing, either the rows fail or you end up creating structure by accident.
- Work on a copy. Keep the untouched export.
- Try a small batch first. Five rows will surface a format problem just as well as five
hundred, and are far easier to unpick.
What can be exported
Beyond employee details, exports cover attachments, attendance attachments and profile pictures, over a date range and in your chosen format. These are the ones to reach for when you need evidence out of KAMI rather than data.
After an import
Check the import history. It records what ran and what happened — the first place to look when the result is not what you expected.
Then run Missing Data. Imports are the most common source of gaps at scale: one column absent from the file means that field is empty on every row it created, and Missing Data finds it in seconds.
Scheduling
Exports can be scheduled rather than run by hand — useful for a recurring feed into another system.
The mistake worth avoiding
The expensive error is importing against the wrong identifier, so rows update the wrong people or create duplicates of people who already exist. It is not obvious immediately, and it multiplies quietly.
This is why the small first batch matters: check that five rows landed on the five people you meant before you run five hundred.