Case Study: Zoom achieves proactive data quality and trusted data products with Bigeye

How Bigeye is helping Zoom achieve their vision of delivering trusted data products to business decision makers

Zoom partnered with Bigeye to improve data quality and pipeline observability as its data systems scaled rapidly to support a wide range of business needs. The Zoom data team, organized in a hub-and-spoke model, was relying on custom SQL checks and manual remediation to catch ingestion failures and data quality issues, which often led to delayed backfills, disrupted workflows, and frustration for analysts and business users.

Bigeye helped Zoom shift from reactive firefighting to proactive data quality assurance using its REST API, Airflow operator, Bigconfig, Autometrics, and metric templates. With Bigeye, Zoom proactively catches and remediates 2–3 data pipeline issues per month, reduces backfill work, and automatically applies comprehensive monitoring to critical tables, helping deliver more trustworthy data at enterprise scale.

Zoom

Tina Chang

Data Engineer