Case Study: Prada Group achieves real-time retail intelligence with Databricks Lakebase

Prada Group cuts infrastructure costs by 50% with Databricks

Prada Group, a luxury fashion company, faced the challenge of fragmented and slow KPI delivery across its global retail brands and channels. Their legacy data systems provided batch updates only a few times a day, leading to outdated information and latency in customer-facing applications. This inconsistency created different versions of the truth for various teams. To address this, they partnered with vendor Databricks to build a modern data foundation.

The solution involved using Databricks, specifically its Lakebase product, as a real-time serving layer for enterprise metrics. This created a unified "KPI factory" where metrics are defined once and exposed as low-latency APIs. As a result, Prada Group unified thousands of KPIs, reduced infrastructure costs by approximately 50%, and achieved a dramatic ~130x faster KPI delivery, cutting response times from seconds to milliseconds. This enables real-time, trusted insights for store associates and digital teams, transforming customer engagement and decision-making.

Prada Group