Gartner defines data observability tools as software applications that enable organizations to understand the state and health of their data, data pipelines, data landscapes, data infrastructures, and the financial operational cost of the data across distributed environments. This is accomplished by continuously monitoring, tracking, alerting, analyzing and troubleshooting data workflows to reduce problems and prevent data errors or system downtime. The tools also provide impact analysis, solution recommendation, collaboration and incidence management. They go beyond traditional network or application monitoring by enabling users to observe changes, discover unknowns and take appropriate actions with goals to prevent firefighting and business interruption. Organizations are looking to ensure data quality across different stages of the data life cycle. However, traditional monitoring tools are insufficient to address unknown issues. Data observability tools learn what to monitor and provide insights into unforeseen exceptions. They fill the gap for organizations that need better visibility of data health and data pipelines across distributed landscapes well beyond traditional network, infrastructure and application monitoring.
"Immediate Data Quality Impact with Great Support"
We like that MC is intuitive and straightforward, making it easy for any new user to jump in (data engineers, software engineers, business). MC efficiently recognizes issues, and informs us through Slack (and MC UI). We can then jump in to investigate before the potential issue escalates. The support team within MC has been excellent as well. They've always been highly responsive. They are also genuinely open to constructive feedback, making it wonderful to work with them.
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set up was straightforward with connectors, ease of use. Design is work in process and could use improvement but easily navigated.
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