---
title: How to handle the GA4 API limitations with Dataslayer
description: Looker Studio has announced this past November 10, 2022 that reports that visualize Google Analytics 4 data are subject to Analytics Data API (GA4) quotas for concurrent requests. Reports that exceed
---
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May 28, 2024
# How to handle the GA4 API limitations with Dataslayer
> ### How to handle the GA4 API quota limits in Looker Studio (Google Data Studio) with the native GA4 connector
### Introduction to give you some context
Looker Studio has [announced this past November 10, 2022](https://support.google.com/looker-studio/answer/11521624?hl=en#nov-10-2022) that reports that visualize Google Analytics 4 data are subject to [Analytics Data API (GA4) quotas](https://developers.google.com/analytics/devguides/reporting/data/v1/quotas) for concurrent requests. Reports that exceed this quota may display the following error message:
**Exhausted concurrent request quota. Please send fewer requests concurrently.**
-May-28-2024-10-38-37-6594-AM.png?width=677&height=248&name=Browser%20template%20(4)-May-28-2024-10-38-37-6594-AM.png)
> ### How can you avoid this or similar quota errors in Looker Studio?
**Although quotas were applied for native Google connectors, in general, partner connectors haven't been affected.**
Usually, a partner connector is connected directly to the official GA4 API, but it has less limitations than the connector created by Google. We recommend the usage of the Dataslayer connectors:
-4.png?width=672&height=246&name=Browser%20template%20(6)-4.png)
The Google Extract Data connector allows you to explore a subset of your data by pulling them from your connectors and storing them as cache for later use. It eliminates the time Looker Studio uses each time it loads your reports, making it load faster. Also, exploring a subset of your data makes it more responsive to work with than with the live connectors.
**Pro Tip: Use [Dataslayer for Looker Studio](https://dataslayer.ai/connectors-dataslayer-google-data-studio) with the Extract Data connector and enjoy the best experiences, efficiency, and performance with these powerful tools.**
However, the Extract Data connector is static, and you should keep refreshing your data sources to maintain freshness. Nonetheless, it is a minor inconvenience as you can use schedules to update your data at specific time frames.
####  You can use Google Sheets as a data storage. It's common that the quotas here have been avoided.
Use our [extension for Google Sheets](https://dataslayer.ai/dataslayer-for-google-sheets), connect your GA4 accounts, schedule refresh all the data you want and [connect the document with Looker Studio](https://support.dataslayer.ai/connect-google-sheets-with-google-data-studio?hsLang=en). As easy as that.
**Take into account that Google Sheets has a limitation of 10M cells. If you are going to store large amounts of data, it's better the usage of a data warehouse like BigQuery.**
****
Nowadays, all the platforms are continuously changing. UA and GA4 are the best example. If you manage large amounts of data and you don't want to loss the access to your historical data, the best solution to secure your data is using a data warehouse. **As we are talking about using Looker Studio as your reporting platform, we recommend you to use BigQuery.**
[Insert your data into BigQuery](https://dataslayer.ai/dataslayer-bigquery), connect BigQuery with Looker Studio, and visualize your data faster than ever. Have it forever.
If you still have doubts or questions, please don't hesitate to contact us via our live chat on our website or via [email](mailto:info@dataslayer.ai).
**Do you continue experiencing GA4 quota errors? Please let us know via our live chat this information:**
- Send us a screenshot showing the error.
- How often does this happen?
- Does it happen to you with a specific query or is it with all of them?
- Does it happen to you with a specific account or is it with all of them?
As always, please do not hesitate to contact us via our live chat on [our website](https://dataslayer.ai/?__hstc=205882892.6526bb15cfac7d661ffbfd3c4281267e.1709723421854.1709899115717.1710148803745.8&__hssc=205882892.8.1710148803745&__hsfp=1885414922) or via [e-mail](mailto:info@dataslayer.ai) if you still have doubts or questions. We are happy to help!
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