Google BigQuery is a paid feature, contact us to try it out.
Benefits
Data Warehouses offers a cheap, flexible and scalable solution for storing and transforming data. Including it in you data pipe opens opportunities for more data blending and high data throughputs while avoiding data silos.
It only takes a couple of minutes to set it up and all you need is a Google account.
These are some cases when you should consider using Looker Studio on top of a Data Warehouse:
You want to have complex Looker Studio reports with a lot of charts and/or fields (and want to avoid rate limiting)
You want to have Looker Studio reports querying heavy data loads with a lot of rows (and want faster report queries to avoid rate limiting)
You want to send the data to multiple reporting tools or for backup and you want it to go through the same pipe for simplicity
You want to join your data with other data that is kept outside of Funnel before using it in Looker Studio
Setup
Login to console.cloud.google.com with your Google account.
Create a Google Project and remember the Project ID that you get.
Go to Billing and select Enable Billing for the created project, read more here.
Login to Funnel and go to the Data Warehouses page and create a new BigQuery Data Share. Use the OAuth authentication for a quick and easy setup and select the fields that you want to include. Fill in the project ID from step 2 and select a name for the Dataset and the Table that will be created for you. We recommend using all the default settings. See more advanced details here.
Click Save and enable the scheduling of the Data Share by clicking on the toggle.
Click Run now.
Verify that the Dataset and Table is created in BigQuery.
Go to Looker Studio and create a blank report.
Use the BigQuery connector to add data.
Input the Project you created and the Dataset and Table that Funnel created for you.
Click "Add" and now you can see the Dimensions and Metrics on your right and can build your report.
The BigQuery setup steps are outlined in more detailed here and include a product tour in BigQuery and instructions for other visualisation tools.