Case Study: Trek achieves 80-90% faster retail analytics and near-real-time ERP replication with Qlik

Trek unifies data and analytics with Qlik and Databricks to gain a holistic view of its business

Trek Bicycle, a global retail and consumer-products company founded in Wisconsin, faced rising costs and sluggish analytics as its legacy data warehouse struggled to scale. Retail reporting often took 30–48 hours and regional processing was siloed, while ERP data was only replicated weekly, leaving stakeholders with stale insights and slow decision-making.

Trek migrated to the Databricks Lakehouse Platform and uses Qlik Cloud Data Integration to replicate ERP and POS data into Delta Lake in near-real time, plus Delta Live Tables and Databricks SQL for streamlined transformations and analysis. The move cut retail analytics run-times by 80–90% (from ~48 hours to 6–8 hours), increased daily data refreshes threefold, moved ERP replication from weekly to near-real time, and delivered a unified, cost-effective view of the global business.

Trek

Advait Raje

Business Intelligence Specialist