Yes, there are data egress charges for using Power BI (cloud) against GCP BigQuery. This is because Power BI is hosted on Azure, which is a different cloud provider than Google Cloud.
Data egress charges are incurred when data is transferred out of a cloud provider's network. In this case, data is being transferred from Google Cloud (where BigQuery is hosted) to Azure (where Power BI is hosted).
The specific data egress charges will vary depending on the amount of data being transferred and the regions where Google Cloud and Azure are deployed. For the most current rates, it's best to refer to the official documentation of both providers.
Here are some tips to potentially reduce your data egress charges when using Power BI against GCP BigQuery:
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Power BI Service Tenant: Consider having your Power BI service tenant in the same region as your BigQuery dataset, although the main cost driver is the volume of data transferred.
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DirectQuery vs. Import Mode: Using DirectQuery can reduce the amount of data transferred, but it might lead to more frequent queries to BigQuery, potentially increasing query costs. Balance the two based on your specific use case.
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Incremental Refresh: Implement an incremental refresh to only refresh the data that has changed, reducing the volume of data transferred.
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Data Compression: While BigQuery results are already compressed when transferred, any additional compression techniques should be evaluated for their effectiveness in further reducing data volumes.
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Third-party Data Gateway: Consider using a third-party data gateway to connect Power BI to BigQuery. While this can help in some scenarios, be aware of the additional complexity and potential latency this approach might introduce.
For more detailed information on data egress charges and best practices, please refer to the following documentation:
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