Messy legacy spreadsheets with inconsistent fields make data migration painful — and vendors lock the fix behind expensive migration support

Summary

Teams inheriting data from a previous tool or organization face a nightmare of inconsistent, non-standardized spreadsheet fields (classification, donor/owner names, dates, IDs) spread across multiple Excel files, old FileMaker/Access databases, and abandoned Dropbox folders. There is no reliable, self-serve way to map these messy, customer-specific columns into the new system: field usage is non-uniform, records for recent years are missing entirely, and the only escape hatch offered by incumbents is expensive, mandatory vendor migration support. This is exactly the 'rebuild a CSV importer for every onboard' pain: the mapping/validation/cleanup work is bespoke per customer, unscoped, and recurring. It is severe because it blocks customer onboarding, costs real money (quoted migration fees), and no purpose-built product lets a small team reliably ingest dirty spreadsheets themselves with column mapping, validation, and error surfacing. Existing tools either punt to manual vendor migration or require heavy upfront metadata normalization.