What is Data Observability? The Definitive Guide

Data observability is the degree of visibility into your data at any point in time, including monitoring, troubleshooting, and ensuring data quality throughout the data stack. It plays a critical role in ensuring that data is available, accurate, and trustworthy by addressing common issues such as data inconsistency, outdated or incorrect data, and data silos. The four pillars of data observability are metrics, metadata, lineage, and logs. Data observability tools can help detect anomalies, implement a robust data CI/CD pipeline, visualize data lineage, and provide insight into how your data is being used. Some popular data observability tools include Metaplane, Monte Carlo, and Datafold.