Data Observability describes the ability to measure the internal state of data systems based only on their outputs. It uses automated monitoring, alerting, and triaging to identify and evaluate data quality and discoverability issues, leading to healthier pipelines, more productive teams, and happier customers. By surfacing data downtime incidents as soon as they arise, the five pillars of data observability provide the holistic framework necessary for true end-to-end reliability. According to Gartner, enterprises will increase their adoption rate of observability tools by 30% by 2024.
