Case Study: Slice achieves scalable data pipelines and machine learning-powered personalization with Fivetran

Slice Brings Machine Learning to Pizza

Slice, a technology platform for independent pizzerias, faced rapidly growing data volumes and the burden of internally writing and maintaining ETL code as it expanded services. To scale reliably and free engineering capacity for product work and analytics, Slice adopted Fivetran for automated data pipelines (feeding a Databricks-backed data lake and Looker BI), replacing fragile, manual data movement with managed connectors and point-and-click syncs.

Using Fivetran to load data into S3/Databricks, Slice eliminated routine pipeline maintenance, saving the equivalent of up to three full-time engineers and enabling the hire of a Director of Data Science and ML hires to build personalization, CRM messaging and a restaurant operating system. Fivetran’s automation reduced failures and latency—Slice’s 3–5 minute SLA target for production-to-reporting is now measured in milliseconds—letting engineers focus on growth-driving projects and predictive analytics.

Slice

Jason Ordway

Chief Technology Officer