How to Consolidate Years of Spreadsheets into Airtable

You are working on a project to centralize a program’s archival data from the 1990s to today.

Over the years, this data was stored in separate spreadsheets, usually one sheet per year. Each year introduced new fields, removed old ones, or changed how data was entered.

Recent sheets contain far more columns than older ones. In total, you are dealing with roughly 50,000 records spread across dozens of files.

Now you want everything in a single table in Airtable.

You are still figuring out the best approach. You do not want to waste weeks doing this the wrong way, only to realize later that the data should have been structured differently from the start.

So what is the correct approach before importing anything into Airtable?

Plan Before You Import Anything

The biggest mistake people make is importing first and planning later. With historical data like this, planning is the real work.

Before touching Airtable, review all your yearly spreadsheets and list every column that exists across them. This gives you a complete picture of how the data evolved over time.

As you do this, you will notice that some columns represent the same information but were named differently, some only apply to specific years, and others are outdated and no longer worth keeping.

This step helps you decide what should be preserved, merged, or removed before any data moves into Airtable.

Design the master table

Once you understand your columns, design the structure of your master table in Airtable.

Decide which fields are part of the core record and which ones are optional or purely historical. Create all required fields upfront, even if older records will be empty for many of them.

This ensures consistency as you import data from different years.

Clean the data inside the spreadsheets

With the table structure defined, clean the data in your spreadsheets before importing anything.

Remove deprecated columns that you have already decided not to keep.

Pay special attention to data formats that Airtable may misinterpret. Dates are a common example.

Values like 20240116 are stored as plain numbers and will not be recognized as dates by Airtable. Use formulas in Excel to convert them into proper date formats such as YYYY-MM-DD before importing.

The more work you do at this stage, the smoother and more predictable the import process will be.

Use the Spreadsheet Import extension

For large imports like this, the best option is the Spreadsheet Import extension.

It saves a lot of pain because it lets you map spreadsheet columns to Airtable fields, even when the column names do not match the field names exactly. This gives you full control over where each column ends up before anything is imported.

Import each sheet directly into your table using the extension, map the fields, and verify the results. Once everything looks correct, complete the import and move on to the next sheet. Repeat the same process for all remaining spreadsheets.

Another advantage of using this extension is that it preserves links during the import, which is especially important if your historical data contains URLs or linked references.