Case Study: Aircall improves data trust and reliability with Monte Carlo

Scaling Data Quality for Innovation and Growth Aircall’s Data Observability Journey

Aircall, a customer communications and intelligence platform, faced a challenge with growing distrust in the internal data provided by its data team. Their initial monitoring could catch technical errors but failed to detect data quality issues, which were often first discovered by stakeholders. This eroded confidence in their data and prompted their search for a data observability solution from Monte Carlo.

By implementing Monte Carlo's data observability platform, Aircall automated monitoring and alerting across its data stack. The solution enabled the team to detect and resolve data incidents faster, often before stakeholders were affected. This significantly improved data reliability and trust. Measurable outcomes included a reduction in the number of incidents seen by stakeholders and the ability to proactively track key data quality metrics like time to resolution.

Aircall

Tanguy d’Hérouville

Lead Data Engineer