Case Study: Car and Classic saves 8+ hours a week identifying data incidents with Metaplane
Key results
The challenge
Car and Classic, Europe's leading classic car marketplace, serves more than 100 daily stakeholders with a two-person data team. Running complex queries on a MySQL database, reports took over 30 seconds to load or failed entirely, and without centralized transformations teammates created conflicting metric definitions. The result was long iteration cycles and degraded trust, with the team even skeptical of raw data.
The solution
The team implemented Snowflake, dbt Cloud, and Metaplane together. Metaplane began automatically monitoring the data after a 15-minute setup, with ML-based monitors and downstream impact analysis making alerts actionable so the team can notify affected functions such as marketing.
“With Snowflake, dbt, and Metaplane, trust in data is a lot higher. As a result, our team is using data to drive the business forward.”
JSJames SharwinHead of Data, Car and Classic
The results, in context
By catching issues proactively, Metaplane saved the team over 8 hours per week and reduced the time to identify data quality issues from weeks to hours. In one case it flagged an anomalous drop in website log data caused by a cron script deleting records older than a year, preventing hard-to-recover data loss. Separately, Snowflake delivered at least a 10x improvement in report load times across the stack.