Business need
Zoomcar required a scalable, cost-efficient data platform
Zoomcar was experiencing rapid growth in both user numbers and data volumes as its peer-to-peer car-sharing marketplace expanded across India. The company’s existing cloud setup required frequent upgrades, came with premium support costs and lacked pricing stability. Scaling computing and storage capacity involved complex cluster expansions, which slowed performance and delayed the delivery insights needed for real-time decision-making. With thousands of tables and multiple database engines in use, data fragmentation made analytics and application development increasingly difficult.
To sustain expansion and deliver a smooth user experience, Zoomcar needed a modern infrastructure capable of handling large, diverse datasets without manual overhead. The company sought a unified data foundation that would help it process bookings, vehicle telemetry, pricing intelligence and customer behavior faster and more reliably. A clear technology vision emerged: consolidate data, automate scaling and adopt managed services that reduce operational burden while enabling rapid innovation. Migrating to Google Cloud’s fully managed platform aligned with that vision. The new platform simplified operations, providing elasticity, performance consistency, and a strong foundation for future AI-driven features and mobility services.
NTT DATA’s deep expertise in large-scale migrations enabled us to modernize seamlessly, without disrupting our operations. Their team led our transition to Google Cloud, simplifying data workflows and building a platform designed to scale with our growing needs. With NTT DATA, we now have the performance and flexibility to confidently support our next phase of growth.”
Solution
Modernizing Zoomcar’s data foundation on Google Cloud
We focused on transforming Zoomcar’s fragmented and resource-intensive environment into scalable cloud-native architecture. Our team worked closely with Zoomcar’s leadership and engineering groups to understand current workloads, operational pain points and future product goals that were tied to mobility growth.
We recommended a phased migration approach to ensure business continuity while addressing the complexity of moving multiple storage systems and analytics pipelines.
By unifying disparate data assets into BigQuery, a unified analytics platform, insights are now generated faster, and it’s much easier for business teams to access important data. Production workloads were re-architected, with fully managed services designed to support different performance and availability needs. Data processing jobs were shifted to an autoscaling environment, eliminating manual intervention and reducing operational complexity.
This approach relied on repeatable migration frameworks, strong governance and continuous optimization to ensure a smooth transition and long-term sustainability. We worked closely with Zoomcar stakeholders to align on cost structures, compliance requirements and future scalability plans.
With a modern cloud foundation in place, Zoomcar now benefits from greater dependability, faster analytics, and a flexible cloud operating model that supports rapid business expansion. The business can now accelerate innovation in shared mobility services and improve the customer experience without the burden of maintaining legacy infrastructure.
Our rapid growth demanded a unified, scalable data platform to enable faster decision-making and power new mobility initiatives. We needed an environment that could evolve with us while unlocking innovation across teams. Today, this modern foundation gives us the flexibility to launch new services, elevate customer experiences, and derive greater value from our data.”
Outcomes
Scalable data platform enables faster innovation and business growth
Scalable performance
- 5,000+ tables consolidated into a single analytics engine
- 20+ databases modernized and optimized through managed services
- Solution supports operations in 90+ countries
Cost and efficiency gains
- 60-70TB of data moved to a cost-efficient storage
- Automated scaling eliminated manual cluster management
Faster innovation
- Unified datasets shorten delivery times for new mobility features
- Cloud-native environment supports future AI and real-time intelligence