Data observability tools enable organizations to understand the state and health of their data, data pipelines, data landscapes, and data infrastructures, as well as the associated financial costs, across distributed environments. This is accomplished by continuously monitoring, detecting, alerting, analyzing, and troubleshooting data workflows to identify and resolve issues, thereby reducing and preventing data issues and system downtime. The tools also provide information on data lineage, collaborations, and incident management. They go beyond traditional network or application monitoring by enabling users to observe changes, discover unknown issues, and take appropriate actions to deliver reliable data and prevent business interruption.
Gartner defines DataOps as the collaborative data management practice focusing on improving communication, continuous integration, automation, observability and operations of data flows between data managers, data consumers, and their teams across the organization. DataOps tools connect and orchestrate data pipelines across heterogeneous systems. Data and analytics leaders are the buyers in this emerging market. The primary audience for DataOps tools is “data manager” personas like, data engineers, data integration developers, operations/incident analysts, database administrators and data architects. The secondary audience is “data consumer” personas like business analysts, business intelligence developers, data scientists and citizen roles (departmental users who are domain experts, but less technical).