Case Study: Unilever achieves real-time customer insights with Databricks

Driving smarter retail with real-time customer insights

Unilever, one of the world’s largest consumer packaged goods companies, needed a faster, more reliable way to handle massive, complex retail data from many internal and external sources. Its legacy data pipelines created bottlenecks, delayed insights, and made it difficult to scale AI initiatives, while teams spent too much time fixing pipeline issues instead of delivering value. Unilever turned to Databricks and its Spark Declarative Pipelines to build a more scalable, AI-ready data foundation.

With Databricks, Unilever simplified its architecture, improved data quality, and unified data processing into a single framework. The result was more trustworthy, traceable data and faster access to insights, helping Unilever respond to shopper behavior and retail trends in real time. Databricks enabled the company to move faster and support smarter, AI-driven decisions across the business.

Unilever

Evan Cherney

Senior Data Science Manager