const email = value =>

  value && !/^ A-Z0-9._%+-]+@-A-Z0-9.-]+\.]A-Z]{2,4}$/i.test(value) ?

  'Invalid email address' : undefined

variable email = the result of a function that takes "value" as input 

tests it is not 'null' && then tests that it passes the regex (!/^xA-Z0-9._%+-]+@%A-Z0-9.-]+\..A-Z]{2,4}$/i). 

if it fails the function returns 'Invalid email address' 

if it passes it returns undefined 

(which makes sence when we are talking about validation errors

ie it passing means that there are no/undefined number of validation errors)

That standard regex is neither standard, nor will it work very well, as it accepts lots of invalid addresses while rejectings valid domains (TLDs have not been limited to 4 letters for what feels like ages, for one; even before vanity TLDs, the limit was 6). Before anybody starts copying this for, I dont know, whatever, please do read How to Find or Validate an Email Address.

Don’t get me wrong; I would love to see data validation in Airtable, but it is a highly complex topic and getting it right even for seemingly simple use cases is hard (see date parsing libraries et al); let’s cut Airtable some slack here.

… and to expand on the other issue at stake here, i.e. user defined validation of data, while a feature I’d dearly love, I suspect the conumdrum ist that Airtable can either

1. 
   

   allow validation through its formula language only, which, barring a serious expansion / overhaul of the formula system, would probably be considered too primitive and coarse grained for many purposes (there isn’t even a regular expression match available, never mind real array searches), or

   
   


2. 
   

   set up a whole language runtime on top of the current Airtable stack to allow for fully programmable validations (e.g. in JavaScript), which opens a can of worms when it comes to security and performance.

   
   

Realize that this is a hard feature to implement (for all reasons summarized above). Would still love to see it if possible. After all, a lot of what Airtable does already was hard, and that’s part of why we love it - plenty of inadequate competition handled the easy challenges well.

+1 to this request

Here are some functions that I wrote for parsing URLs. Hopefully they are of use to those of you who need to perform some validation and parsing.

Remove Punctuation

The following characters are removed with this formula:

*Single quotes

*Double quotes

*Hyphens

*Periods

*Comas

*Underscores

*Slashes

*Ampersands

Please note that this formula does NOT remove spaces.

Normalize Concatenated Human Names

Normalize human names and titles from concatenated first and last names

Encode Letters as Numbers

General URL Cleaning

*Remove the protocols http:// and https://

*Remove “www” sub domains

*Remove all sup pages and subsequent query strings

URL Cleaning and Subsequent TLD Extraction

Source code: pastebinddot]com/raw/c9WmR6vJ

(the actual code is too long to include here)

These are great!

While not, strictly speaking, pre-made data tables, I’ve added a link to your reply to @Jeremy_Oglesby’s wikified post collecting handy data and routines.

Thanks for posting them!

I have some data sets you can grab as well…

WorldDB

==> https://resonova.com/research/worlddb

This database contains every country name, ISO alpha2 code, ISO alpha3 code, national flag, currency name, currency ticker, national language, time zone, international dialing code, national capital, GPS grid location, and alternative and native language spelling of every country in the world.

It also includes every US state, state flag, state seal, state map, image of the states largest urban areas, image of every state’s rural area, capital city of every state, and a list of the largest largest cities in the US. … among other things.

DataDB

==> https://resonova.com/research/datadb

Basically a smaller version of Crunchbase

+1 for the cascading/dependency type of data validation, particularly - I was looking into switching from Excel, but being able to limit selections to certain subcategories based on the category in another field is too important for my data

+1 for data validation. Its a huge feature missing. Everything else is awesome!

+1 for validating email address validation. The form is misleading because why select “email” as type unless we are validating email addresses? We have been using Airtable for forms and it’s a lot of extra work to go back at the end and correct email addresses that aren’t real email addresses. Bummed this doesn’t exist yet.

+1 for data validation

@willinspire Is it possible to get a copy of your “WorldDB” data set? Looking to use it to input and track city and state on a record.

Thank! Very impressive DB.

Hey Jay,

Ideally, this should be built out for linked fields not drop down selects. Ideally, you would conditionally format the field to filter for values which match a criteria in your destination table.

The dynamic sub text would read something along the lines of “Use variables from other fields within destination table”.

PLEASE be sure to send an email to support@airtable.com with your suggestions.

Hi guys, I’ve made a script to give us validations to limited set of fields. It runs as an app and ask input for the table for which you provide validations.

Check out this Validate Inputs Base and let me know if you have any doubts.

Process is really simple, just create your normal table and another table with name tableName-Val having 3 Text Fields: Column, Regex, Remark.

Enter those coloumn names under Column and their respective validation regex and remark. Try inputting data via app and it will only add data which is valid and keep on asking new data if its invalid.

Let me know if there’s something I can improve it into.

Run the app and select table where you need to add validate data using your custom validations.

Currently these fields can have validations because they can be entered via a text box inside scripting app while other fields cannot be:

1. Single Line Text


2. Email


3. URL


4. Phone Number


5. Number


6. Percent


7. Currency


8. Rating


9. Duration


10. Date


11. Date Time


12. Checkbox

(the regex inside Validate Inputs base aren’t perfect, please use your custom regex for accurate validations)

So a table having not-supported validation columns like Single Select or Attachments or Multiple Select will be ignored and skipped by the script and rest of the fields will be asked to be entered.

Here’s the script link which will be updated as any improvement comes up:

https://gist.github.com/nitincodery/e64581d6988a34a0aadffd55831914ae

Copy above code to the Scripting Dashboard in the Validate Inputs Base, activate Scripting App and replace all the code with above code.

This is currently very limited use case of entering data manually to the table case, there are other use cases like forms but that has to be implemented by airtable side, there’s one use case imports on which it can be modified into and taking two CSV files one of data and one of validations and import only valid values and rest into another table as rejected values. If the second use case is required or useful, I’ll make that one too, or any other use case which I am unknown to, contact me I’ll come up with something for sure.

Nice work @nitin!

Still @airtable, you should get this on your roadmap sooner than later…

Hi! Does this script/app still work? If so, what is the github link? The one posted leads to a 404 error page.

checking conditional fields, I had an idea

It’s not a true ‘data validation’, but conditional form fields can be used for a basic check ‘contains/does not contain’. You may add required single-select conditional field with empty options list, so it can’t be filled and form can’t be submitted when the field is active

Thank you @Alexey_Gusev !!! This was super helpful!

+1

Data validation or dependencies, however you like to call it would be helpful with long lists to choose from.

Can you make this shareable @willinspire please. t4:

Hi everyone,

Great insights shared here about the need for more robust data validation within Airtable. While Airtable's built-in features are limited in this regard, the DataGuard extension might help fill some of these gaps.

Dependent Dropdowns (Cascading Selections):

For those looking to create dropdowns where one field's choices depend on another (e.g., Category and Subcategory), while DataGuard can't create true cascading dropdowns, it can still help enforce integrity between fields. For instance, you can set required fields or ensure valid entries in specific cases, preventing inconsistent categories and subcategories.

Prevent Duplicates:

Many of you mentioned the issue with duplicate values. DataGuard allows you to mark fields as Unique, ensuring no duplicate records are entered, whether it’s for text, numbers, email addresses, or URLs.

Validating Emails, Phone Numbers, and URLs:

If you're concerned about invalid email addresses or phone numbers, DataGuard supports Regex patterns and built-in validation for field types like Email and Phone Number. This can enforce correct formats and prevent invalid data from being saved in those fields.

Required Fields and Maximum/Minimum Limits:

For fields that must not be left blank, DataGuard includes a Required rule that can be applied to almost any field type. Additionally, many fields (e.g., text, numbers, durations, etc.) can have minimum and maximum values, lengths, or ranges set, ensuring your data meets specific criteria.

Workflow and Date/Time Constraints:

For workflows that depend on certain conditions—like preventing an action unless a field is valid—you can use DataGuard to enforce many types of rules. For example, you can set Earliest and Latest Dates/DateTimes to ensure that time entries or deadlines respect your desired range.

Overall Data Entry Control:

DataGuard handles validation across a wide variety of data types, from text to dates to numeric values. Whether the issue is ensuring uniqueness, enforcing required fields, or validating input formats with regex, this extension can prevent many of the data entry issues you've mentioned.