Case Study: JetBlue Improves Data Trust and Data NPS with Monte Carlo

How JetBlue Used Data Observability To Help Improve Internal “Data NPS” By 16 Points Year Over Year

JetBlue, the airline operating more than 1,000 flights a day across 100+ destinations, needed a more reliable way to ensure its data was accurate, on time, and trusted as it expanded its modern stack on Snowflake, Databricks, Fivetran, dbt, and Tableau. After migrating off an on-premise database, the company faced greater scrutiny from internal data users and needed better visibility into data quality at scale.

JetBlue implemented Monte Carlo’s data observability platform to automatically monitor volume, freshness, schema, SQL-based checks, dimension tracking, and field health across thousands of tables, while also adding lineage and alerting into Microsoft Teams for incident response. With Monte Carlo, JetBlue improved operational handling of data issues and increased its internal Data NPS by 16 points year over year, while also tracking stronger data trust and user engagement across the organization.

JetBlue

Brian Pederson

Manager of Data Products