Google Data Studio connector for Airtable

What is the CURRENT, BEST WAY to sync data REAL TIME, AUTOMATICALLY from AT to Data Studio. These forums are always super dated and incomplete and cobbled together. Would be nice to NOT have to parse through all the out-dated methods if there are NEW ways to do things. Are we still farting around setting up a sync to Sheets or is there a better mousetrap?? Please advise most recent methods. Thanks. :slight_smile:

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Hi everyone. I had this problem too. But I searched for some add-on to connect Airtable to Google Sheets, and I found that one: https://gsuite.google.com/u/0/marketplace/app/couplerio/532272210531?hl=pt&pann=sheets_addon_widget

It allowed me to connect many bases (even from different workplaces) in a single Google Sheet that can be used at Data Studio.

The most funny part is that this add-on refresh all the data automatically and replace the information, instead to create a new row.

Some images:

Another point: it’s for free, but it has limits.

image

You can create 1000 imports per month and 50.000 rows per month. Every month, it resets.

But, to be honest, it’s a lot of imports and rows per month.

I hope it helps you, guys!

This is very helpful!! Thank you so much

Hey Everyone,

I wanted to let you all know about an easier way to connect Airtable to Google Data Studio - Sync Inc (syncinc.so).

With a couple clicks, we’ll setup a hosted Postgres follower database containing all your Airtable data. We keep your database in sync in real-time. All you have to do is connect your Sync Inc database to Google Data Studio with the standard Postgres connector.

2020-12-16 20.37.02

As we all know, Google Data Studio has first class support for PostgreSQL. By turning your Airtable base into a Postgres database, you can plug you Airtable data into GDS in not time.

If you’re curious about how it all works, check out our docs: https://docs.syncinc.so/

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Yes it is an excellent tool to organize marketing data , NOW everyone can utilize the best tool provided by Google . Computerize gathering all promoting information and limit time spent on getting ready and organizing. Optimize ROI by looking at the whole customer Journey . If you are not aware of this tool and really dont know how to implement then you can visit this url , which explain you everything https://www.windsor.ai/best-google-data-studio-connectors/

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if you want to get in depth information then please visit the website https://datastudio.google.com/

here you will get all relevant information from scratch to implementation

thanks to google once again.

Thanks to everyone who’s commented on this post. It sure can be challenging to visualise data from Airtable and I wish we could say… a few years later… that we’ve solved the problem, but alas! Airtable for some reason doesn’t want to create what everyone actually needs, which is a frontend on their database! So you’re not always dropped in to a myriad of tables/views/fields/records etc etc. Although we still use Airtable, anytime we need a frontend to make sure people only get access to the info/metrics they need without having to navigate lots of data, we tend to develop on another product which I’m not sure is appropriate to mention here but who’s logo is listed on our website if you’re interested.

Hi everyone,

We at TheDataStudents have also developed a Google Data Studio connector for Airtable that you can use to retrieve data live from your bases (max delay of 15min) so in addition to all of the other solutions mentioned above, you now have a direct way to connect to your data and use it in GDS reports! For more information head over to our dedicated Airtable connector page. Any questions or feedback welcome!

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I haven’t tried it yet, but this looks promising as there is a free version

Hi folks, chiming in on this old (yet still active & relevant) topic.

I’m helping a client connect their data to Data Studio, and we’ve been exploring several solutions, including some mentioned in this thread above. Here’s our experience so far, & would love to hear recent suggestions or experiences from other folks.

TL;DR: there are no truly “good options” out of those we’ve tried, but we’d love to be proven wrong.

We also talked to Airtable support just this week, who said they were not aware of any plans for a 1st-party integration between Airtable & Data Studio (which would be the best solution).

1. Export to Sheets, connect Sheets to Data Studio

This worked reasonably well, but we wanted to avoid more ad hoc code dependencies to pull data from the Airtable API & write it to Sheets. We’d also like to avoid another redundant dataset (in Sheets) which we’d have to monitor for parity & data quality etc.

There are 3rd party services which sync Airtable to Sheets as well (as mentioned elsewhere in this thread). We have not explored these (or other DB sync options) for the reasons above. We’d prefer a direct connection without redundancies, especially if using a paid service.

2. Third party "Community Connector"

Airtable published this blog post in October 2021: How to connect Airtable to Tableau, Google Data Studio, and Power BI.

They suggest 2 options for Data Studio, neither of which are 1st party integrations maintained by either Airtable or Google. There is a hosted option & a self-hosted option. Again, we’re trying to avoid more ad hoc integrations that we must maintain, so we opted to trial the hosted option.

However, I had trouble following the link to the community connector they recommend in the article (by “Airtable Labs”), & when I finally found it, was unable to authorize it in Data Studio. So instead we tested a different community connector that appears in the Data Studio interface:

This is the connector by TheDataStudents mentioned by @Raul_Garcia above. There is currently a 7-day free trial, after which it costs $10/month.

This does successfully connect Airtable data to Data Studio, but it has been so sluggish as to be unusable for us (connecting to tabs with several thousand records), where every interaction takes 2-3 minutes for the data to update.

Performance is much better when used in combination with Data Studio’s Extract Data data source, as recommended by the TheDataStudents FAQ page. But this has its own limitations & requires additional steps & complexity in the setup.

Conclusion (for now):

This is where we are currently, & will continue to test this method in lieu of a better solution. Would love to hear about better options from the community! (And even more, would love a 1st party integration here, as we conveyed to Airtable support).

Hi Daniel,

Many thanks for your post and all the detailed and constructive feedback you have provided. We think it’s pretty useful for all the readers!

With regards to our connector, we believe your feedback is fair, as we are limited by GDS quotas and Airtable API’s calls limits. It’s worth mentioning that we rely on the customer’s Google account to store all the data so that their data is not even visible to us, increasing data protection. We are trying all we can to improve the performance and many of our customers are successfully using the connector already. Many of them may not have very big tables and others are using features that we have developed to try to help in this situation, in addition to the “Extract Data” option. Those are:

  • The possibility to extract Airtable views: this allows customers to build a view including only the records they want to extract. In essence, this reduces the number of rows that the connector extracts.

  • The possibility to choose the fields to be extracted. In essence, this reduces the number of columns that the connector extracts.

These options can be used when creating the data source. They have been recently developed but we should have added those to our FAQs. We will do so shortly.

We will update this post in the future as we come up with new ways to improve performance and please feel free to reach out to us on hello@thedatastudents.com if you would like to discuss further.

Many thanks again!

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Hi Raul,

Thanks for the response & for your work on this connector, fulfilling an obvious need of the community!

It’s helpful to know about the other options you mention, which might result in similar performance as the Extract Data source, with at least one less layer of data sources to manage. We will experiment with this as well.

One problem we might encounter is that it seems that only one account is authorized to create the Community Connector, which might become a bottleneck in the process. Currently, once they create the connector data source to a table with all fields included, they can share access to the data source, & the rest of the team can use the Extract Data source to select the fields they currently need. Not sure if there is a similar way to enable team self-sufficiency with the connector alone, without every team member having a paid subscription? (or sharing a single account)

Thanks again!

Hi Daniel,

Many thanks for your comments.

Not only can those features be used as an alternative to Extract Data but also in combination for faster performance if needed.

We always encourage teams to share the data source set up by the owner of the account. If you select to share with ‘Edit’ permission, they should be able to update the primary data source (not create new ones) and link it to Extract data as you mention:

The user without a DataStudents account will see a message similar to the one below, but they will be able to make changes to the data source (while they wouldn’t be able to if they were trying to create a new one).

On the other side, we need to limit the users to one GMail/Google Workspace account per subscription: Otherwise, we would have, for example, agencies using one subscription to connect data for many of their clients.

Thanks a lot!

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Thanks Raul!

That makes sense, understand wanting to limit agencies using a single subscription for many clients. This does create a bit of a workflow bottleneck for small teams though, especially if there is already hesitancy to bring on another paid 3rd party service.

But such is the modern SaaS landscape I suppose.

Thanks again for your replies!