Hello Team,
I’ve encountered several challenges with the BigQuery connector that are impacting its readiness for production. Below, I detail these issues and suggest potential improvements:
Dataset Selection
Currently, the Clockify connector defaults to creating datasets in the US region under randomly generated names, presumably based on customer names. This setup requires us to implement additional processes for renaming and transferring these datasets to suit our regional needs (e.g., EU). It would be beneficial to have the ability to specify the dataset region and naming conventions directly during setup.
Naming Convention
The schema used in BigQuery includes table names with spaces and represents time intervals as strings. This format introduces unnecessary complexity and potential errors. A more standardized approach using underscored naming and actual timestamp data types would greatly simplify integration and usage.
Error Reporting
The lack of detailed error feedback when exporting data to BigQuery is concerning. Simple notifications like Export of the following failed: Time Entry are insufficient to diagnose issues. Enhancing the system to provide detailed error reports, including the number of rows affected, would significantly improve troubleshooting and reliability.
Data Integrity
There appears to be a discrepancy between the data reported in Clockify and what is inserted into BigQuery, suggesting issues with data completeness. For example, certain time entries referencing clients and projects do not sync correctly, leading to inconsistencies. Ensuring complete and accurate data synchronization is critical for maintaining trust in the system.
Support System
Despite raising multiple tickets regarding these issues, I have not received adequate support. Timely and effective communication is crucial for resolving such critical issues. Improved customer support and technical assistance would be greatly appreciated.
We are keen on continuing to use this tool, but we’re struggling to get any level of comprehensive reporting out of it.