How Data Teams Are Using Data Observability for Trust

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How Data Teams Are Using Data Observability for Trust

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Episode 88 of The Data Business Podcast explores how data teams are adopting data observability to rebuild trust in their pipelines. Lucas and Luna dive into a specific case: a mid-sized e-commerce company that reduced data incident detection time from hours to under four minutes using a three-pillar observability stack—freshness, volume, and schema monitoring. They discuss the cost of bad data, the tension between speed and reliability, and why observability is becoming a non-negotiable layer for modern data platforms. The episode also covers how observability tools integrate with existing data catalogs and lineage systems, and why treating data pipelines like software systems changes the game for data engineers. No fluff, just a concrete look at one team's journey from firefighting to proactive data quality management. #DataObservability #DataQuality #DataTrust #DataPipelines #DataEngineering #DataCatalogs #DataLineage #FreshnessMonitoring #VolumeMonitoring #SchemaMonitoring #DataIncidents #MonteCarloData #FexingoBusiness #BusinessPodcast #BusinessAndTechnology #DataInfrastructure #Analytics #InformationProducts Keep every episode free: buymeacoffee.com/fexingo

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