Google BigQuery connectors & integrations

Connect 325+ data sources to BigQuery with our production-grade ELT pipelines.

Windsor.ai’s Google BigQuery integration enables data teams to ingest high-volume marketing, CRM, and analytics data with zero maintenance and no coding.

Get schema-consistent, analytics-ready tables delivered directly into your BigQuery environment in under 5 minutes — fully optimized for advanced SQL querying, machine learning workflows, and BI tools.

30-day free trial No credit card needed
Join over 4,000 businesses that trust Windsor.ai to automate Google BigQuery data integration
audi logo
colgate
asics
roche
UBS
unicef
verisure
wpp
club med
skoda
heineken
puma
audi logo
colgate
asics
roche
UBS
unicef
verisure
wpp
club med
skoda
heineken
puma

Our popular Google BigQuery connectors

Automatically send your data from these sources into Google BigQuery using Windsor.ai.

Adobe Analytics (v1.4)

Adobe Analytics (v2.0)

Amazon Vendor Central

Apple Search Ads

Azure Table Storage

Blended Data Connector

Brevo (Sendinblue)

Commission Factory (Awin)

Facebook Lead Ads (Meta)

Google Ad Manager

Google Campaign Manager 360 (CM360)

Google Display & Video 360 (DV360)

Google Merchant Center

Google PageSpeed Insights

Google Search Ads 360 (SA360)

Instagram Public Data

LinkedIn Business Manager

Microsoft Dataverse

Microsoft Dynamics 365

MNTN (mountain.com)

Paypal Transaction

Pinterest Organic

Plausible Analytics

Rakuten Advertising

Salesforce Marketing Cloud

The New York Times

Twilio TaskRouter

Twitter Organic (Legacy)

Walmart Marketplace

Wikipedia Pageviews

Yahoo! Finance Price

YouTube video

How to set up BigQuery data integration with Windsor.ai

Explore our step-by-step documentation to automatically integrate your data into BigQuery with the Windsor.ai no-code ELT connector.

Connect once and let your data update automatically on your preferred schedule.

1

Prepare your BigQuery environment

Ensure you have access to BigQuery in your Google Cloud account.

bigquery environment
bigquery environment
selecting data source in windsor.ai
google bigquery destination windsor.ai
bigquery integration
bigquery data integration

Accelerate your data workflows with Windsor.ai’s BigQuery integration

Windsor.ai provides a reliable, fully automated ELT solution for ingesting, transforming, and syncing multi-channel data into Google BigQuery — with key features including:

  • Data centralization
  • End-to-end, fully automated ELT architecture
  • Advanced workflows
  • Enhanced data security
  • Omnichannel source ingestion: Connect 325+ marketing, CRM, and SaaS platforms (e.g., Google Ads, Meta, HubSpot, Shopify, Salesforce) into a single BigQuery project.
  • Consistent data modeling: Windsor.ai auto-aligns schema types and naming across disparate systems to ensure query compatibility and modeling consistency.
  • Cross-domain unification: Maps and consolidates user- and event-level data from different tools into normalized tables for advanced reporting.
bigquery data integration windsor.ai
  • Native schema and table optimization: Automatically creates tables with standardized naming conventions and data types, supporting partitioning and clustering to reduce long-term query costs.
  • Schema drift resilience: Tracks upstream changes and auto-adjusts schema while maintaining downstream model and query stability.
  • High-throughput support: Engineered for daily/hourly refreshes across large, multi-source datasets with minimal latency.
  • Modern data stack compatibility: Fully interoperable with dbt, Looker, and other BI tools for seamless downstream analytics.
windsor.ai interface
  • Automated reporting pipelines: Schedule recurring data loads and deliver analytics-ready tables to BigQuery with no manual updates.
  • SQL-based machine learning: Train and deploy models inside BigQuery using BigQuery ML — no need to move data out of the warehouse.
  • Built-in orchestration support: Automate workflows via native scheduled queries or integrate with Cloud Composer for DAG-based ELT control.
reporting schedule in bigquery
  • Comprehensive audit logging: Track all data access and modification events for compliance and monitoring.
  • Granular access control: Role-based permissions ensure only authorized users can access sensitive data.
  • Built-in disaster recovery: Google’s infrastructure provides high availability and automatic failover for uninterrupted data access.
  • Regulatory compliance: Windsor.ai’s integration maintains strict adherence to GDPR, HIPAA, and other relevant data privacy standards.
soc2 windsor
Data centralization
  • Omnichannel source ingestion: Connect 325+ marketing, CRM, and SaaS platforms (e.g., Google Ads, Meta, HubSpot, Shopify, Salesforce) into a single BigQuery project.
  • Consistent data modeling: Windsor.ai auto-aligns schema types and naming across disparate systems to ensure query compatibility and modeling consistency.
  • Cross-domain unification: Maps and consolidates user- and event-level data from different tools into normalized tables for advanced reporting.
End-to-end, fully automated ELT architecture
  • Native schema and table optimization: Automatically creates tables with standardized naming conventions and data types, supporting partitioning and clustering to reduce long-term query costs.
  • Schema drift resilience: Tracks upstream changes and auto-adjusts schema while maintaining downstream model and query stability.
  • High-throughput support: Engineered for daily/hourly refreshes across large, multi-source datasets with minimal latency.
  • Modern data stack compatibility: Fully interoperable with dbt, Looker, and other BI tools for seamless downstream analytics.
Advanced workflows
  • Automated reporting pipelines: Schedule recurring data loads and deliver analytics-ready tables to BigQuery with no manual updates.
  • SQL-based machine learning: Train and deploy models inside BigQuery using BigQuery ML — no need to move data out of the warehouse.
  • Built-in orchestration support: Automate workflows via native scheduled queries or integrate with Cloud Composer for DAG-based ELT control.
Enhanced data security
  • Comprehensive audit logging: Track all data access and modification events for compliance and monitoring.
  • Granular access control: Role-based permissions ensure only authorized users can access sensitive data.
  • Built-in disaster recovery: Google’s infrastructure provides high availability and automatic failover for uninterrupted data access.
  • Regulatory compliance: Windsor.ai’s integration maintains strict adherence to GDPR, HIPAA, and other relevant data privacy standards.

FAQs

What is BigQuery?

BigQuery is a fully managed, cloud-based data warehouse developed by Google that enables you to handle multi-engine, multi-format, and multi-cloud data, making it a versatile solution for modern data challenges.

With powerful business intelligence (BI) and artificial intelligence (AI) capabilities, this tool significantly enhances big data analytics so businesses can make informed, impactful decisions. By reinforcing BigQuery integration with advanced technical workflows, organizations can go beyond basic analytics to build comprehensive machine learning models and unlock deeper insights.

Tired of manually transferring data to BigQuery? Try Windsor.ai today to automate the process

Access all your data from various sources in one place. Get started for free with a 30-day trial.
g logo
fb logo
big query data
youtube logo
power logo
looker logo