Advanced analytics teams rely on GA4 raw data for deeper funnel insights, debugging, and modelling. Most organisations run these workloads in Azure. The problem is that GA4 only exports to BigQuery. The moment you export, you’re operating across two cloud platforms.
It’s a situation we often see: Azure-first organisations need GA4 raw data but also a clear, controlled way to integrate Google Cloud Platform (GCP) into their setup.
This guide outlines the practical options available and helps you choose the approach that best fits your diverse team's needs, workflows, and governance models.
In this article, we cover:
Handling all core activities in a single cloud environment while integrating a second platform, such as Google Cloud Platform (GCP) for GA4 raw data access, creates a challenge for many companies. As demand for advanced analytics grows, managing a multi-cloud infrastructure becomes essential. Organisations must decide how to run and integrate these environments with confidence and clarity.
We regularly see organisations that run their IT and analytics workloads in Azure but need GA4 raw data to solve advanced use cases: debugging complex tracking issues, building custom marketing funnels, or powering detailed reporting models. Many teams turn to a monitoring tool like Cloud Nine Digital’s GA4 Monitor at this point, as it gives them clearer visibility over live tracking anomalies before those issues cascade into multi-cloud pipelines.
BigQuery, part of Google Cloud, is the only destination for GA4 raw data export. Even if your business operates entirely in Azure, you still require GCP + BigQuery as the entry point for GA4’s event-level data. Introducing GCP adds integration work, governance considerations, and decisions about how this new environment fits into your existing Azure setup. This is typically where Cloud Nine Digital’s dedicated compliance team steps in to help organisations navigate the legal and data-processing implications of adding a second cloud platform.
From here, organisations typically move toward one of three multi-cloud models.
A dual-cloud setup establishes two active cloud environments, each serving a distinct purpose. Marketing, performance, and data teams often benefit from the flexibility of BigQuery, while IT and BI teams maintain structured processes and controls in Azure. This split reflects the natural tension between agility and governance: one environment enables fast experimentation, while the other offers long-term stability.
How the data flows
GA4 → BigQuery → transformations in BigQuery → downstream activation or warehousing in Azure
Benefits
Challenges
Pro tip: Using a tool like Cloud Nine Digital’s Data Layer Monitor ensures that the data entering BigQuery is structurally consistent, preventing downstream breakages during cross-cloud transfers.
Many organisations want to keep final analytics and reporting in Azure tools such as Synapse, Data Lake Storage, or Power BI. In this pattern, GCP acts as a preparation layer, handling only what Azure cannot do natively.
How the data flows
GA4 → BigQuery → light aggregation / preparation → export to Azure → modelling in Synapse / Databricks / Data Factory
Benefits
Challenges
Schema drift in GA4 can create additional pressure on the GCP preparation layer. Automated alerts from monitoring your data lake / data warehouse would help teams detect these changes before they cause breaks in Azure ingestion jobs.
Some organisations prefer the simplest possible multi-cloud footprint. GCP acts only as a conduit: it receives GA4 data and passes it straight into Azure with minimal processing.
How the data flows
GA4 → BigQuery → export to Azure → full modelling and transformation in Azure
Benefits
Challenges
Here’s a quick rule of thumb:
Regardless of the model, keep these in mind.
Do I need GCP to access GA4 raw data?
Yes. BigQuery is the only export destination for GA4 event-level data.
Can I send GA4 data directly to Azure without GCP?
No. You must land the data in BigQuery before exporting it elsewhere.
What is the simplest architecture for GA4 + Azure?
The “passing window” model: GCP receives the data, Azure processes it.
Which Azure tools work best with GA4 data?
Common choices include Azure Data Lake Storage, Azure Data Factory, Synapse, Databricks, and Power BI.
Does GA4 data need to be prepared before Azure?
Often yes. GA4’s nested schema benefits from light transformation in BigQuery before landing in Azure.