BigQuery as the central warehouse for your marketing data
Serverless data warehouse for marketing data. EU region as default, native GA4 binding, cheaper than Snowflake for analytical workloads under 1 TB/month.
BigQuery vs Snowflake for marketing
For marketing-analytics workloads under 1 TB/month, BigQuery is simply cheaper. Snowflake bills compute minutes, BigQuery bills bytes. The GA4 raw export lands directly in BigQuery (no middleman), and Google Ads / Search Ads 360 have native connectors. For a marketing stack, that saves 2–3 integrations.
Snowflake becomes the better choice at mixed enterprise workloads (analytics + app data + ML features) where multi-cloud or cross-region sharing matters.
EU region, not optional
BigQuery datasets must be created explicitly in europe-west1 (Belgium) or europe-west3 (Frankfurt). The default is US, and GA4 exports automatically write to the dataset's region. Miss this and you unintentionally land on US cloud, in doubt, in violation of your own privacy policy.
Our BigQuery setup
- Ingest: GA4 raw export, Google Ads, Funnel.io (for Meta/TikTok/LinkedIn), Stape event logs
- Modelling: dbt Core, CI via GitHub Actions
- Governance: row-level security, separate datasets per use case, BigQuery admin dashboard
- Cost control: date partitioning, slot reservations from ~€2k/month spend
- BI layer: Data Studio (free) or Looker (enterprise) depending on governance requirements
Topical context
- BigQuery GA4 export
- BigQuery EU region
- marketing data warehouse
- BigQuery cost
- dbt BigQuery
- BigQuery integration agency
- BigQuery implementation
Is your data ready for activation? The Data Readiness Audit answers it before campaigns depend on it.
Request a Data Readiness Audit →Is the GA4 export to BigQuery GDPR-compliant?
Yes, if the BigQuery dataset sits in an EU region (europe-west1 Belgium or europe-west3 Frankfurt) and the Google DPA is signed. By default the dataset is created in the US, that has to be changed actively. Without an EU region and DPA there's no clean GDPR path.
What does BigQuery cost for a typical marketing stack?
For GA4 export plus ad data at medium volume (10–50 M events/month): €50–€300 per month. Storage is ~€0.02/GB, queries €5/TB. With partitioning and slot reservations from ~€2,000/month spend, the cost stabilises, before reservations, budget discipline matters.
Can BigQuery connect directly to Looker, Power BI, or Tableau?
Yes, all three have native BigQuery connectors. Data (Looker) Studio is free and the default entry point for GA4 data. Power BI and Tableau need a service account, and at high data volume slot reservations to prevent dashboards from becoming query-cost drivers.
More integrations we work with
- Data WarehouseSnowflakeCloud data warehouse with a multi-cloud option and an EU region. The alternative to BigQuery when your cloud strategy calls for it.
- Data WarehouseClickHouseBlazing fast columnar database for real-time analytics. Open-source, self-hostable in the EU.
- Data Integration & ETLfunnel.ioMarketing data hub with 500+ connectors. Harmonises ad, CRM, and analytics data before BigQuery or Snowflake, without custom ETL.
- Data Integration & ETLFivetranManaged-ELT heavyweight with 900+ connectors. Reverse-ETL native since the Census acquisition, end-to-end data movement from one place.
- Data Integration & ETLdbtTransformation layer for the warehouse. Versioned SQL models, tests, and lineage instead of hand-maintained reports and SQL sprawl.
- Data Integration & ETLAirbyteOpen-source challenger to Fivetran. A massive ecosystem of community connectors for long-tail APIs.