Connecting a BigQuery Warehouse
  • 18 Aug 2021
  • 1 Minute to read
  • Dark
    Light
  • PDF

Connecting a BigQuery Warehouse

  • Dark
    Light
  • PDF

Google BigQuery

Connecting Precog

  1. In the Panoply navigation menu, click BI Connection. This displays your Panoply data warehouse's connection details. 
  2. Download the .json credentials file.
  3. Sign into your Precog account.
  4. Click the Destinations
  5. Search for Panoply BigQuery
  6. Click the Panoply icon.
  7. Name the destination.
  8. Enter the dataset you wish to send the data to.
  9. Upload the .json file you downloaded in step 2.
  10. Click on Add.
  11. Select which tables you wish to connect to this destination.

Connecting Stitch

  1. In the Panoply navigation menu, click BI Connection. This displays your Panoply data warehouse's connection details. 
  2. Download the .json credentials file.
  3. Sign into your Stitch account.
  4. Click the Destination tab.
  5. Click the Google BigQuery icon.
  6. Scroll to the Your service account section.
  7. In the Your Key File field, click the icon and locate the JSON credentials file you downloaded in Step 3. Once uploaded, the BigQuery Project Name field will automatically populate with the name of the GCP project in the JSON project key file.
  8. Select a Google Storage Location by using the Google Cloud Storage Location dropdown, then select a US region.  
Note

Changing this setting will result in replication issues if data migration isn’t completed correctly.

9. There are two definitions for the loading behavior:

* Upsert: Existing rows will be updated with the most recent version of the record from the source. With this option, only the most recent version of a record will exist in Google BigQuery.
* Append: Existing rows aren’t updated. Newer versions of existing records are added as new rows to the end of tables. With this option, many versions of the record will exist in Google BigQuery, capturing how a record changed over time.

Note

Loading behavior can’t be changed after the destination is created. To change Google BigQuery loading behavior, you’ll need to delete and re-create the destination.
This setting may impact your Google BigQuery costs. Learn more.

10. Click Check and Save. Stitch will perform a connection test to the Google BigQuery database; if successful, a Success message will display at the top of the screen. This test may take a few minutes to complete.


Was this article helpful?