Data Observability Technology Provider PEAK Matrix® Assessment 2025

Data teams face rising complexity, from hybrid and multi-cloud pipelines to growing AI workloads. Hidden data failures, cost overruns, compliance breaches, and bad downstream decisions are becoming untenable. As a result, data observability is no longer optional; it is now a strategic imperative. Modern platforms now leverage ML to detect anomalies, monitor schema drift, and trace lineage across structured tables and unstructured data sources.

While enterprises are increasingly embedding gen AI across platforms through anomaly triaging recommendations and monitor suggestions, capabilities around automated anomaly resolution remain nascent and require strong governance and human oversight. As these features mature, data pipelines are expected to evolve from passive monitoring setups to intelligent systems that proactively manage and resolve issues, enhancing resilience in AI-driven data environments.

In this report, we assess 19 data observability technology providers featured on the Data Observability Technology Providers PEAK Matrix® 2025. Each profile comprehensively highlights the provider’s key strengths and limitations.