Building a Reliable Data Platform Based on Data Observability скачать в хорошем качестве

Building a Reliable Data Platform Based on Data Observability

In this session, Starburst partners with Assurance IQ to explore how to build a reliable and scalable data platform by integrating Trino and data observability practices. Designed for data professionals, this presentation highlights the critical role of observability in ensuring data quality, operational efficiency, and stakeholder trust—especially at scale. You’ll hear how Assurance evolved from a fast-moving data-centric startup into a sophisticated organization operating in the highly regulated insurance and financial services space. As their data ecosystem expanded to support millions of daily predictions and a growing network of contributors, the need for strong observability practices became paramount. This talk outlines how the team uses Trino as the core query engine and Monte Carlo to monitor data quality across the platform. Topics include building data trust through schema validation, anomaly detection, lineage mapping, and accountability through domain ownership. The presenters also detail how to structure observability programs around people, processes, and tools, providing actionable strategies for deploying alerts, enforcing quality checks, and scaling observability across teams. Whether you’re just beginning your observability journey or looking to advance your current practices, this presentation offers a practical and technical roadmap for building robust, transparent data platforms. #DataObservability #Trino #MonteCarloData #DataEngineering #DataQuality #AnalyticsEngineering #DataOps #ModernDataStack #StarburstData #DataPlatform #DataTrust