Case Study: Auto Trader Achieves Scalable Data Trust with Monte Carlo

How AutoTrader UK Migrated to a Decentralized Data Platform with Monte Carlo

Auto Trader, the UK and Ireland’s largest digital automotive marketplace, was migrating to a modern, cloud-based, decentralized data platform while trying to maintain trust in data quality for hundreds of internal users. As the team moved from centralized data operations to self-serve ownership, it needed a way to prevent data downtime, reduce bottlenecks, and ensure reliable reporting across a complex stack that included BigQuery, Looker, dbt, Kafka, Airflow, and more.

Monte Carlo provided data observability across Auto Trader’s platform, adding automated monitoring, alerting, and lineage for BigQuery and Looker. Auto Trader used Monte Carlo for volume, freshness, schema, and ML-driven statistical checks, plus incident routing to the right team channels. The result was faster incident detection and resolution, better downstream impact analysis, and greater visibility into “unknown unknowns,” helping Auto Trader scale data trust and support its self-service model.

Auto Trader

Edward Kent

Principal Developer