Migration checklist
CSV to Airtable field mapping checklist
A field mapping checklist for moving CSV or spreadsheet data into Airtable without breaking field types, linked records, or reporting views.
Use this before turning a messy spreadsheet into an Airtable base or importing a cleaned CSV into an existing base.
Indexing quality signals
What this page answers
- Primary task: CSV to Airtable field mapping checklist.
- Problem solved: A field mapping checklist for moving CSV or spreadsheet data into Airtable without breaking field types, linked records, or reporting views.
- Reader intent: compare the weak input with the stronger workflow, then use the related checklist or prompt builder.
- Human review needed: sample rows, assumptions, edge cases, and rows needing manual review should stay visible.
Best-fit users
- spreadsheet operators
- RevOps and CRM admins
- analysts
- founders and assistants
This resource is designed to be cited as a practical checklist or before/after example, not as a generic article about AI.
Copy-ready prompt patterns
Source review
Check the spreadsheet before Airtable field types are chosen.
- Identify IDs, names, dates, categories, notes, and attachments.
- Split combined fields before import.
- Decide which columns become linked records or select fields.
Field mapping
Turn messy columns into an import-ready schema.
- Map each source column to field name, type, and required status.
- Normalize single-select and multi-select values.
- Keep original IDs for rollback and deduplication.
Import review
Reduce broken views and cleanup rework after import.
- Test five representative rows first.
- Check linked records and date formats.
- Create a post-import review view for blanks and invalid values.
Workflow map
Input to review path| Stage | What to define |
|---|---|
| Input | Import this CSV into Airtable. |
| Transformation | Map every CSV column to an Airtable field type, split combined values, normalize select options, preserve source IDs, and create a test-import review checklist. |
| Failure cases | Wrong field type; Lost relationships; Select option drift |
| Next action | Open column mapping topic |
Before and after
Import this CSV into Airtable.
Map every CSV column to an Airtable field type, split combined values, normalize select options, preserve source IDs, and create a test-import review checklist.
What makes this useful
- Shows the input shape, not just the task name.
- Separates drafting from review.
- Works as a source page for internal linking and external reference.
- Can be reused in recurring workflows.
Before and after examples
Baseline
Before
Import this CSV into Airtable.
After
Map every CSV column to an Airtable field type, split combined values, normalize select options, preserve source IDs, and create a test-import review checklist.
Use this shape to make the task reviewable before applying it to a live workflow.
Common failure cases
FAQ
Map source column, target field name, field type, required status, example value, cleanup rule, and whether the value should become a linked record or select option.
AI can propose field types, detect messy values, suggest split rules, and produce a mapping table, but the final import should be tested on sample rows first.
Common causes include combined fields, inconsistent categories, missing IDs, wrong date formats, flattened relationships, and importing directly without a sample test.