Explanation:
If you are trying to connect your source to Looker Studio, the ability to visualize data correctly may depend on the volume of data you want to display. If you encounter the “COMMUNITY CONNECTOR ERROR” there are two potential causes:
- Data Type Discrepancy (Less Common):
This issue occurs when one or more data fields have been assigned an incorrect data type before creating the report. Ensuring that all fields have the correct data type can help resolve this problem.
- Exceeding Looker Studio’s Data Size Limit (Most Common):
The most frequent cause of this error is attempting to visualize files or data columns that exceed 100MB in size. According to Looker Studio’s documentation, this is a limitation when processing large volumes of data (see screenshot).
It is worth mentioning, that a key indicator to quickly see if your extracted data size exceeds the limit is that Looker Studio won’t even allow you to proceed to the field selection stage to define data types to then create the report.
To accurately check the size of your source file, Dataddo provides this information in the Source Detail section, right under the source name (see screenshot).
If the source exceeds 100MB, it will be highlighted in yellow, making it easy to spot potential issues depending on the destination you want to connect it to.
Let’s see now which alternatives we have to solve this issue.
How to Fix:
- Optimize Data extraction (Create a new optimized source):
The number of records, the number of columns, and the size/complexity of values in each column are key factors that determine the overall source size. To optimize it:
- Extract only the fields relevant to your use case.
- Avoid redundant data, as it consumes resources that may be needed in the future.
Keep in mind that if your source is close to the 100MB limit and continues receiving new data daily, you will eventually reach the limit and encounter the same error.
To prevent this issue in the long term, we recommend considering the solution in section two below.
- Consider Using a Data Storage/Warehouse:
Some APIs—especially those provided by CRMs—offer limited data filtering options at the extraction source. This forces our connector to extract large volumes of data, which can lead to the mentioned errors and limitations, particularly when trying to visualize data in dashboarding apps.
To avoid these limitations, we highly recommend sending data to a data storage or warehouse first. These environments are designed to:
- Handle large amounts of data efficiently.
- Provide advanced filtering tools to optimize datasets before visualization.
If you still need to visualize this data in a dashboarding app, you can connect it to Dataddo to automate the entire process and avoid future limitations.
If you need further information on this topic, please do not hesitate to contact your Dataddo account manager or our Solutions Team.