The challenge
The client's data was spread across Google Analytics, first-party systems and external sources, with no single governed place to bring it together.
Reporting, data science and AI work each needed the same data, but quality, security and compliance were handled differently from team to team.
What we did
- Designed a landing zone on Cloud Storage and automated ingestion orchestrated and scheduled with Managed Airflow.
- Built a BigQuery data warehouse in bronze, silver and gold layers, taking data from raw to cleaned to business-ready.
- Enabled AI and data science on the same platform with BigQuery ML, an agent platform and Gemini GenAI models.
- Put data governance at the core: data catalog, data quality, data profiling, data security and data compliance.
- Served the gold layer to Power BI, AI-enabled analytics, Looker Studio and APIs.
- Ran it all on a shared Google Cloud foundation: Cloud IAM, monitoring and alerts, Cloud Logging, notifications, GitHub, Cloud Run, Cloud KMS and Secret Manager.
The result
One governed data platform that every team draws on, from dashboards to AI models.
Consistent data quality, security and compliance across the whole flow, from landing zone to consumption.
A foundation ready for AI-enabled analytics and GenAI use cases.
At a glance
