A global enterprise facing rapid digital expansion required a modern data platform capable of supporting real-time analytics, omnichannel operations, and scalable AI workloads. The organization struggled with a legacy on-premises data warehouse that was costly to maintain, difficult to scale, and unable to process growing volumes of transactional and streaming data. Fragmented data sources, slow batch processes, and limited analytical capabilities hindered decision-making and operational efficiency. To unlock enterprise-wide insights and accelerate digital transformation, the company partnered with O2 Technologies to build a cloud-native data platform that enabled unified data ingestion, near real-time analytics, secure governance, and scalable AI-readiness.
The outdated data ecosystem could not support modern digital and AI-driven use cases.
O2 Technologies engineered a robust, future-ready data platform leveraging a cloud-native lakehouse architecture. The design incorporated high-performance compute clusters, scalable storage layers, and a domain-oriented data model that supported advanced analytics and AI workloads. A unified semantic layer ensured consistent reporting across global business units, while multi-region deployment provided availability, resilience, and low-latency access. This architecture established a flexible, scalable foundation capable of powering enterprise-wide digital transformation.
O2 implemented modern, automated ingestion pipelines supporting batch, streaming, and CDC-based data flows. These pipelines unified data from ERP, CRM, operational systems, IoT devices, and partner APIs, enabling near real-time insight generation. Streaming pipelines captured transactional and event-based data as it occurred, while batch workflows efficiently handled historical loads and high-volume datasets. For the first time, the organization gained access to reliable, timely data across all business functions.
To eliminate fragmentation, O2 deployed a modern lakehouse that consolidated raw, curated, and analytical datasets within a governed structure. Version-controlled tables, schema enforcement, zero-copy cloning, and time-travel capabilities enabled auditability, reproducibility, and lineage visibility. Optimized storage formats improved query performance, reduced latency, and supported advanced analytics workloads. This strategy unified all enterprise data into a single, trusted source of truth.
O2 established enterprise-grade governance aligned with global compliance and security requirements. Role-based access controls, encryption, identity management, and automated quality validation ensured reliability and protection of sensitive data. FinOps best practices—such as auto-scaling, workload scheduling, and tiered storage—optimized cloud consumption and reduced unnecessary costs. Audit-ready monitoring and lineage tracking supported operational transparency and regulatory adherence across all regions.
The cloud-native data platform modernization delivered transformative enterprise outcomes. Real-time processing replaced slow batch workflows, and the organization gained a unified view of its operational and analytical data. Reporting speed improved by 50%, while cloud optimization efforts reduced storage and compute costs by more than 40%. With an AI-ready foundation, the enterprise is now equipped to scale predictive analytics, automation, and advanced decision intelligence. The organization operates with a resilient, modern data infrastructure capable of supporting long-term digital expansion and innovation at global scale.