Data-powered car-sharing gives people the freedom to drive
GetGo Carsharing, Singapore's largest car-sharing company, migrated to the Databricks Data + AI Platform to unify telemetry, payment and image data from over 300,000 drivers and 3,000 vehicles. Using geospatial analysis and natural language processing, GetGo reduced fuel theft by 50% by detecting fraudulent refueling patterns, accelerated time to insights by 66%, and cut time to market for new data products by 20%.
Overview
GetGo Carsharing, Singapore's largest car-sharing company, migrated to the Databricks Data + AI Platform to unify telemetry, payment and image data from over 300,000 drivers and 3,000 vehicles. Using geospatial analysis and natural language processing, GetGo reduced fuel theft by 50% by detecting fraudulent refueling patterns, accelerated time to insights by 66%, and cut time to market for new data products by 20%.
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Inspect the highlighted sourceThe challenge
GetGo Carsharing was pushing data to a MySQL Community Edition database with no way to govern access or know who was using data for what, requiring shared admin passwords and manual downloading, emailing and storing of data in shared drives. Without an enterprise-grade solution they could not scale efficiently, ensure data security, or implement AI and machine learning, and complex manually intensive infrastructure maintenance meant it took one week to deliver insights to business units and partners.
The solution
GetGo Carsharing migrated to the Databricks Data + AI Platform on AWS, choosing Delta Lake over native services like Redshift to avoid the added effort, labor and cost of recreating what Delta Lake already provided. Unity Catalog gave controlled data governance and security, growing adoption among business data users from five to 40 and the data team from five to 20 without productivity degradation. Using Databricks Lakeflow Jobs with a GitHub staging branch to test jobs before production, the team orchestrates data pipelines reliably, consumes insights through Power BI dashboards, builds custom applications on Databricks SQL, and uses Photon to accelerate queries. The platform applies geospatial analysis and natural language processing for faster insights, and analyzes each user's booking behavior and refueling patterns to identify fraudulent fuel-card misuse.
Reported business value
GetGo Carsharing achieved a 20% boost in data team productivity, accelerated time to insights by 66%, and now delivers next-business-day insights across all use cases, a 7x improvement from their legacy environment. Geospatial analysis lets them optimize vehicle placement and fleet composition to balance supply and demand, and identifying fraudulent booking and refueling patterns has helped reduce fuel theft by 50% and increase customer satisfaction.
Sources
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