This session dives deep into a real-world retail success story, showcasing how a leading retail brand in Nordics unified its data landscape across multiple Nordic and Baltic countries. Facing the challenge of fragmented data silos and complex cross-border data sharing, the company leveraged the power of Google Cloud's BigQuery and Analytics Hub to build a centralized, scalable, and cost-effective data platform.
We'll explore how they:

Conquered data fragmentation: Consolidated disparate data sources from various countries into a single source of truth in BigQuery, enabling comprehensive analysis and reporting.

Streamlined data sharing: Utilized Analytics Hub to securely share and access data across different departments and external partners, fostering collaboration and data democratization.

Optimized ownership and cost: Implemented Analytics Hub's granular data sharing capabilities to clearly define data ownership and allocate costs effectively, ensuring transparency and accountability.

Modern data transformation: Leveraged Dataform, a powerful alternative to DBT, for efficient and collaborative data modeling and pipeline orchestration.

Automated deployments: Built a robust DevOps and CI/CD pipeline using Workload Identity Federation, GitHub, and Terraform Cloud, enabling rapid and reliable deployments.

This session is suitable for cloud architects, data engineers, and developers interested in advancing their understanding of AI agents and serverless solutions on Google Cloud. Prior experience with Google Cloud services like BigQuery, Vertex AI is beneficial but not required.
Session duration is ideally 30–45 minutes to cover technical depth and live demos.
Previous presentations include Google Cloud Nordics Summit, DevFest 2023, Google Cloud Next 2024, and Öredev.