Transferring to and storing data in the EU location

If it's important for your business to store user data you collect into Google BigQuery with OWOX BI within the European Union, you can transfer the existing data from the US (United States) to the EU (European Union) multi-region locations.

In this article, we describe three possible methods of how you can do it.

Important: Once you transfer your data to a different location, you need to adjust your pipelines to make them send data to the new tables. Read the details below.

To move your Google BigQuery data to a different location, use one of the following methods.

Method 1. Use the dataset copy feature in Google Data Transfer (now in beta)

The newest method provided by Google. The feature is free while in beta. It lets you copy datasets in the same region or across regions. The feature is a part of BigQuery Data Transfer Service, so make sure you have it enabled.

Read the detailed guide to copying datasets in the BigQuery documentation.

Method 2. Use a Google Cloud Storage bucket

You need to create new datasets located in the EU location a Google Cloud Storage bucket which will be the destination for the old dataset data and the source for the new datasets.

  1. Create a new dataset in the EU location as described in Google Cloud Platform documentation.
  2. Create a storage bucket, a Google Cloud Storage container to store the table data from the US datasets.
  3. Export the table data into the created bucket with the following settings:Table_export.png
  4. In the EU dataset, create a table that references an external data source and transfer your data from Google Cloud Storage.

Each table should be exported separately.


That's it. Now your data is stored in the EU.

Changing OWOX BI Pipeline set-up based on the new dataset location in Google BigQuery

After you move data to the EU location, go to your OWOX BI project and complete the following steps:

  1. Delete the Google Analytics Cost Data → Google BigQuery pipeline that is connected to the user behavior data pipeline.
  2. Delete Google Analytics User Behavior Data → Google BigQuery pipeline.
  3. Create a new user behavior data pipeline with the EU dataset. A new cost data export pipeline will be created automatically.

Once you delete the old pipelines (see steps 1-2), it is important to create the new ones (see step 3) as soon as possible to minimize the hit data loss during the configuration change.

  1. If you have active Ad platforms → Google BigQuery pipelines, make sure they collect data to EU datasets. Otherwise, delete old pipelines and create new ones with the EU datasets.
  2. Also, you need to check whether the EU datasets are selected as data sources for Attribution models (i.e. transaction data and custom events data) and Smart Data reports. Otherwise, you should adjust the data source settings.

After you complete the settings, contact us at We'll need your project name and names of the tables in the EU location to check if all the processes work correctly. 

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