| Sumario: | By 2025, the estimated global volume of data is expected to reach 180 ZB, more than double the amount collected in 2020. Yet despite data's increased presence and value within organizations, solutions for ensuring data quality have received little attention. This report examines how adequate observability combined with best practices for data logging and monitoring can help organizations efficiently redistribute their management of data quality and analytics. Kensu CEO Andy Petrella explains how a data observability solution will help your IT and data teams detect and stop incident propagation by tracking and measuring data usage performance across systems, projects, and applications in real time. You'll discover how data observability makes it much easier to find and fix the root cause of problems. Learn how to monitor applications that collect, copy, and modify data Detect anomalies based on historical data information Leverage lineage and historical data information to find an incident́??s initial cause Use automated logging and tracing of data and data pipelines to evaluate quality and identify issues Apply DevOps practices to achieve greater visibility, confidence, and speed at the data level Explore how data observability influences team dynamics.
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