Case Study: Mindbody Achieves End-to-End Data Trust with Monte Carlo

How Mindbody Achieves End-to-End Data Trust with Monte Carlo

Mindbody, a company that relies heavily on data to power its product and analytics, needed a better way to spot data issues before they caused problems. Before working with **Monte Carlo**, the data team had no reliable way to identify irregularities like missing or duplicated data until it was too late.

**Monte Carlo** implemented its data reliability platform to monitor Mindbody’s Redshift and Tableau environments for anomalies such as null values, duplicate data, schema changes, freshness, and volume issues. As a result, Mindbody can monitor 15+ high-priority tables across 3,000+ automated tables, improve data trust, and ensure customer-facing data is accurate.

Mindbody

Alex Soria

VP of Data & Analytics