Building a scalable data stack: 3 lessons from Backcountry

Backcountry, a premium online retailer of outdoor gear and apparel, shares key lessons on using a modern data stack to overcome data silos, complexities with legacy systems and improve its customer experience. The company's data engineering team has built and leveraged a modern data stack in three ways: automating data ingestion and pipeline maintenance, building a simple and integrated modern data stack, and developing a data strategy that supports AI and ML. By doing so, Backcountry has reduced pipeline issues by 30%, decreased the time spent on pipeline maintenance, improved accuracy of data being provisioned, and enhanced their AI and ML capabilities.

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