Snowflake-based data platform allows real-time analytics and fleet optimization for shared mobility
With presence across Europe and North America, Wunder powers real-time operations, user engagement, and fleet optimization for mobility operators worldwide.
A scalable, cloud-native data warehouse solution was implemented using Snowflake, leveraging it’s native connectors to integrate Wunder Mobility’s data pipelines for high-performance analytics and unified operational visibility. Terraform was used to automate the deployment of Snowflake objects and infrastructure components.
Year: 2024
A robust platform was needed to ingest diverse operational data, unify it for analytics, and support dashboards, BI, and future data applications, without building custom ingestion pipelines.
Data from real-time vehicle sensors, user interactions, trip logs, maintenance events, and other structured sources were ingested continuously, processed in Snowflake, and made query-ready for downstream consumption. In addition, we set up the infrastructure to enable secure data sharing with Wunder Mobility’s clients using Snowflake’s native Secure Data Sharing capabilities, allowing seamless, governed access to curated datasets without data movement.
To ensure reliability and maintainability, we structured the transformation logic using Snowflake dynamic tables, which enable automated data updates, support incremental processing, and simplify complex data workflows. This approach reduced operational overhead while ensuring data consistency across the platform.
The platform was hosted on AWS, leveraging Snowflake’s separation of storage and compute to achieve elasticity, concurrency, and optimized cost management.
Partnership outcomes
As part of the solution, historical data was offloaded from the operational database into Snowflake, allowing the operational systems to focus solely on current workloads. This significantly improved performance and responsiveness on the transactional side while enabling rich analytical capabilities on the Snowflake platform.
Self-service analytics has been improved, and teams across operations, product, and executive reporting can now explore trusted, up-to-date data with minimal delay. The schema ensures consistent data models, enforceable rules, and clear lineage for auditability.
The modern architecture dramatically reduces ingestion and transformation maintenance overhead while enabling future capabilities such as embedded analytics, secure data sharing, and AI-powered insight generation.
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