Google BigQuery in Polar: your models, governed and blended.
Point Polar at the datasets in your Google BigQuery lakehouse and their columns become governed metrics and dimensions, blended with Shopify, Meta and Google and served to every dashboard, report and AI answer. Read-only is enough, and no one has to write SQL to use the models your data team already built.
/Setup Guide
How to Connect Google BigQuery to Polar.
01 · What you need
A Polar account with Shopify
A Polar account with Shopify connected. This connector plugs in right next to your stack.
Connect your data →A read-only Google BigQuery role
A read-only role Polar can query, and the tables or models you want to expose.
Open Google BigQuery →The Polar team to map it
Polar's AI Data Engineer maps your datasets into the semantic layer so columns become governed metrics.
02 · Bring Google BigQuery into Polar
1
Request Google BigQuery in Connectors ~ minutes
Custom connections available.
In Polar, open Connectors. Google BigQuery sits under Custom connections available: click Request and Polar's AI Data Engineer builds it, in minutes.
2
Map to the semantic layer automatic
Columns become governed fields.
Polar's AI Data Engineer maps your datasets into your semantic layer, blended with Shopify, Meta and Google.
3
Use it everywhere the payoff
No SQL required.
Your modeled datasets, cost tables and KPIs behave like any other source, no re-modeling, no duplicate pipeline, no SQL.
Side by side
Google BigQuery holds the models. Polar makes everyone use them.
Your data team modeled KPIs and cost logic in Google BigQuery, but using them still means SQL or an analyst request. Polar turns those models into governed metrics the whole team can use, blended with your stack.
Google BigQuery on its ownon its own
+Google BigQuery with Polarblended
Using a model means SQL or an analyst ticket.
Modeled columns become governed metrics, no SQL.
Lakehouse metrics live apart from marketing and revenue.
Blended with Shopify, Meta and Google in one layer.
Definitions drift between the lakehouse and dashboards.
One definition, served everywhere the same way.
AI can't reason on models without bespoke pipes.
Governed metrics available over the Polar MCP.
The Gap
The Google BigQuery connector is only half of it.
Once your Google BigQuery models are connected to Polar, you can use them wherever you already work. Ask Polar in plain language, pull them live through the Polar MCP, or schedule a snapshot into the report your team reads every morning.
Google BigQuery
models, cost tables, KPIs
Polar
governed, blended, no SQL