Michele Piunti

Prada Group's advanced analytics and KPI calculations had evolved across multiple disconnected systems, each serving different teams and use cases. This fragmentation made it difficult to maintain consistent definitions, reuse existing logic, and deliver a single trusted view of performance across the business. As data volumes and reporting demands increased, the organization needed a way to reliably manage and compute thousands of KPIs across regions, product categories, and time periods while still providing fast, decision-ready insights. To address this, Prada Group implemented a unified analytics architecture supported by Lakebase as its central data foundation. Lakebase consolidated previously siloed data into a single governed and scalable environment, enabling high-volume storage, efficient querying, and low-latency KPI computation. On top of this foundation, a standardized KPI model and microservices-based APIs provided consistent, easily accessible analytics across departments and systems, transforming fragmented reporting into a trusted, enterprise-wide capability for data-driven decision making.