Case Study: Lendly reduces manual troubleshooting time by 30% with Pantomath

Lendly’s data team reduces manual troubleshooting and reverse engineering time by 30% with Pantomath

Lendly, an online lender, faced a significant challenge as its data team was spending 30% of its time manually identifying, debugging, and reverse-engineering issues within its data pipelines. This reactive process, which often began with alerts from business users, stretched the team thin and prevented them from focusing on more strategic work. They needed a way to gain visibility across their entire data stack, including Fivetran, Snowflake, dbt, and Tableau.

By implementing Pantomath's end-to-end data observability and traceability platform, Lendly's team gained complete visibility into their data pipelines. Pantomath monitors data in motion and at rest, auto-detects issues, and provides real-time alerts. This solution saved the data team 30% of their time previously spent on manual troubleshooting, allowing them to proactively ensure data reliability and focus on revenue-generating analytics.

Lendly

Rob Brichler

Chief Technology Officer