Case Study: Whatnot achieves self-serve data trust and reliable scaling with Monte Carlo data observability

Enabling a Self-Serve Data Culture at Whatnot with Data Observability

Whatnot, a rapidly growing livestream shopping platform, faced the challenge of scaling its self-serve data culture. With over a thousand dbt models and a complex data pipeline, they needed to ensure data reliability and trustworthiness for their non-technical users without creating bottlenecks for their small data team. To address this, they turned to the vendor Monte Carlo for a data observability solution.

Implementing Monte Carlo's data observability platform provided Whatnot with automated monitoring, alerting, and end-to-end lineage. This solution allowed the team to identify and resolve data issues quickly, validating their assumptions and preventing upstream changes from impacting downstream users. As a result, Monte Carlo helped Whatnot maintain a flat rate of data incidents despite exponential growth in platform usage and adoption, ensuring their data remained democratized and trustworthy.

Whatnot

Emmanuel Fuentes

Engineering Director