You can give everyday users a safe, flexible way to import spreadsheets into FileMaker without exposing your database structure. Kyo Logic’s free Custom Import Tool add-on maps friendly column labels to real fields, saves reusable import templates, and loads every file into a staging table first, so users can preview and fix the data before it reaches your real records.

Here is the moment it exists for. Every Monday, purchasing imports a vendor price sheet. This week the vendor added a column and moved “Unit Cost” two places to the right. The pre-mapped import script does not notice. Four hundred items now show a freight charge as their cost, and nobody finds out until a quote goes out wrong.

Why are FileMaker imports hard for everyday users?

Most FileMaker systems offer one of two import paths, and neither is ideal for a non-technical user.

• A pre-mapped import script is simple, but rigid. If a column is renamed or reordered, it breaks or quietly puts data in the wrong field.
• FileMaker’s built-in import dialog is flexible, but it shows users back-end field names, table structure, and naming conventions they should not need to understand.

Real files make it worse. Columns get renamed. Extra columns appear. Some rows should be skipped. One column holds two pieces of data. A user should not have to call a developer because a spreadsheet has one extra column.

What the add-on does out of the box

The Custom Import Tool sits in the middle. A full-access user defines friendly header options once, so an end user sees “Customer Email” instead of a field name like Customer::cust_primary_email. From there the workflow looks like this:

Out of the box the tool supports up to 20 columns, and more can be added if you need them.

Templates that bend without breaking

If a vendor, customer, department, or outside system sends files in a consistent format, users save that structure as a template and reuse it. When a file arrives a little different, they adjust the column order or mark a column to skip. If the change is temporary, they make a one-time adjustment without changing the saved template.

Preview before you commit

A bad import straight into production can create duplicates, overwrite good values, or put information in the wrong fields. Staging the data first gives users a safe place to look. Skipped rows and skipped columns are highlighted, and the staging table is open for edits, so users can clean up values or remove rows before the final step.

Create and update records in one import

With match fields configured, one import can update records that already exist and create new ones where no match is found. That is useful for customer lists, inventory counts, product catalogs, order updates, and membership lists, where some rows are new and some are changes.

Ideas for how to use it

• Vendor price sheets: one template per vendor, adjusted when a vendor changes its format.
• Inventory counts: stage the counts, review the differences, then update.
• Customer and prospect lists: match on email or account number, update the rest.
• Order data from outside systems: map their column names to your fields once.
• Cleanup before go-live: review and correct legacy data before it reaches the new system.

Developers can extend it with scripting, for example splitting a single “Full Name” column into first and last name, or parsing a combined address into street, city, state, and ZIP. Once data is in, the Audit Log & Version History add-on can record what changed afterward, and the Data File script steps handle the export side.

What this could look like in your solution

For most teams, the first template is the import someone dreads every week. Once that one runs from a template with a preview step, the developer stops getting calls about it, and the person running it stops worrying about it. Messy data is often the real problem behind unreliable reports, and controlled imports are one of the cheapest places to stop it at the door.

Kyo Logic builds custom Claris FileMaker and manufacturing software for businesses across New England and beyond. If you want help setting up match logic, building parsing rules for a difficult file, or deciding which recurring imports to template first, reach out.

Frequently asked questions

How do I let users import data into FileMaker without seeing field names?

Map friendly column labels to real fields ahead of time. The Custom Import Tool lets a full-access user define those labels so end users choose names like Customer Email instead of back-end field names.

Can I preview an import before it changes my records?

Yes. The tool imports the file into a staging table first. Users can review, edit, and skip rows or columns, and skipped items are highlighted, before the final import runs.

Can one import create new records and update existing ones?

Yes. With match fields configured, the import updates records that already exist and creates new records where no match is found.

How many columns does the Custom Import Tool support?

Up to 20 columns out of the box, with the option to add more if needed.

Quick takeaways

• List the imports your team runs every week and template the most painful one first.
• Use a staging step for any import that touches records people rely on.
• Pick a reliable match field, such as an account number or email, before you allow updates.
• Download the add-on and run one real file through staging to see what it catches.