Case Study: Contentsquare reduces data incident detection time with Monte Carlo

How Contentsquare Reduced Time to Data Incident Detection by 17 Percent with Monte Carlo

Contentsquare, a fast-growing global data company, needed a better way to trust and manage the reliability of its data as teams scaled quickly. The Data Governance team was spending too much time on manual data quality checks, struggling with dashboard downtime, and facing slow detection and resolution of data incidents. To address this, Contentsquare turned to Monte Carlo’s data observability platform.

With Monte Carlo, Contentsquare automated anomaly detection, business rule checks, alerting, and incident workflows across its Snowflake-based stack and existing tools like Tableau and Atlan. The results were strong: Contentsquare reduced data incident detection time by 17% and time to resolution by 16% in just one month, while data incident documentation increased by 46%. Monte Carlo also helped improve ownership and trust across the organization, giving teams earlier alerts and more confidence in their data.

Contentsquare

Otávio Bastos

Global Data Governance Lead