Looker Studio is a powerful data visualization and exploration tool that enables businesses to gain valuable insights from their data.
However, occasionally users may encounter issues when attempting to connect Looker Studio to their data sets.
The usual error message displayed is “Data Set Configuration Error, Data studio cannot connect to your data set. Failed to fetch data from the underlying data set“
In this article, we will explore some common reasons why Looker Studio might fail to connect to your data set and provide practical solutions to resolve these issues.
Why Looker Studio Cannot Connect To Your Data Set?
In a specific case involving an existing BigQuery data source, where both the data source and dashboard had previously functioned smoothly, an unexpected connectivity issue arose.
Interestingly, the underlying BigQuery table could still be queried successfully through the BigQuery web UI.
Upon editing, the affected data source, all existing fields were visible without any problems. Attempts were made to reconnect the data source but to no avail.
The persistence of the error despite the reconnection attempts added to the perplexity of the situation.
How To Fix Looker Studio Cannot Connect To Your Data Set?
Here are several potential solutions to help resolve the issue:
1. Make Fewer Requests
If you are exceeding the token limit of 5,000 per hour, consider reducing the number of widgets on a page. Simplify the design and avoid excessive widget usage to ensure you stay within the limit.
2. Limit The Number Of Concurrent Users
To prevent exceeding the token limit, it is advisable to either limit the number of concurrent users accessing the Looker Dashboard or refrain from embedding Looker on pages with high traffic.
By reducing the number of users accessing the dashboard simultaneously or avoiding embedding it on heavily visited websites, you can alleviate the strain on the token limit.
3. Stagger Scheduled Reports
Implement a staggered schedule for sending out reports.
Instead of sending all reports at once, distribute them over different time intervals.
This approach ensures a more balanced usage of tokens and helps avoid overwhelming the system.
4. Connect GA4 To BigQuery
To overcome limitations and unlock additional features, such as increased token limits, consider connecting Google Analytics 4 (GA4) to BigQuery.
This integration may require the assistance of a developer and a small monthly budget for hosting the data and reconfiguring Looker.
To connect Google Analytics 4 (GA4) to BigQuery, follow these steps:
- Access the Admin section in Google Analytics.
- Ensure that you are in the correct account and property.
- In the Property column, navigate to “PRODUCT LINKS” and click on “BigQuery Links.”
- Click on “Link.”
- A list of projects for which you have at least read permission will be displayed. Choose a BigQuery project from the list.
- If you have linked Analytics and Firebase or plan to do so, it is recommended to export to the same Cloud project. This facilitates easier data joins with other Firebase data.
- After selecting the project, click “Confirm.”
- Choose a location for the data. Note that if your project already has a dataset for the Analytics property, you cannot configure this option.
- Click “Next.”
- Select “Configure data streams and events” to specify which data streams to include in the export and to exclude specific events from the export. You can exclude events by clicking “Add” to select from a list of existing events or by clicking “Specify event by name” to choose existing events by name or specify new event names that have yet to be collected on the property.
- Click “Done.”
- If you want to include advertising identifiers for mobile app streams, select “Include advertising identifiers.”
- Choose either a Daily (once a day) or Streaming (continuous) export of data, or both.
- Click “Next.”
- Review your settings and configurations.
- Finally, click “Submit” to establish the connection between GA4 and BigQuery.
5. Consider Google Analytics 360
For enterprise-level requirements and higher data limits, Google Analytics 360 is available but comes with a significant cost.
Starting at $150,000 per year, this premium solution provides access to advanced analytics features and may be worth considering if your business requires extensive data analysis capabilities.