![]() Select a Google Storage Location by using the Google Cloud Storage Location dropdown, then select a US region.Once uploaded, the BigQuery Project Name field will automatically populate with the name of the GCP project in the JSON project key file. In the Your Key File field, click the icon and locate the JSON credentials file you downloaded in Step 3.Scroll to the Your service account section. ![]() Select which tables you wish to connect to this destination.Enter the dataset you wish to send the data to.This displays your Panoply data warehouse's connection details. In the Panoply navigation menu, click BI Connection. ![]() See the Install and configuration guide for more details. For more information about pricing for locations, see BigQuery pricing. Pricing for storage and analysis is also defined by location of data and reservations. The Linux and Mac refresh token script has been updated to Python. This page explains the concept of location and the different regions where data can be stored and processed. The connection dialog now automatically retrieves a refresh token, eliminating the need for a manual copy-and-paste of the confirmation code. Type the name of the account, for example datagrip, in the Role section, select the BigQuery BigQuery Data View, BigQuery. Make sure you have the right project selected, then click on the Create service account button. This is because the user account flow has changed and no longer supports the deprecated out-of-band flow. First, let’s get all the details needed to connect to BigQuery from the Cloud Console. The 2.5.x release is still supported for bug fixes and critical security updates, but new BigQuery features will only be added to the 3.x release.Ĭaution: To comply with the Google deprecation of the out-of-band (OOB) authorization flow, ODBC version 2.5.2 introduces changes that may require you to reauthenticate and/or recreate your connection strings. We recommend that you upgrade to the 3.x release.
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