Bringing observability to the modern data stack
You can’t manage what you can’t measure. Just as software engineers need a comprehensive picture of the performance of applications and infrastructure, data engineers need a comprehensive picture of the performance of data systems. In other words, data engineers need data observability.
Data observability can help data engineers and their organizations ensure the reliability of their data pipelines, gain visibility into their data stacks (including infrastructure, applications, and users), and identify, investigate, prevent, and remediate data issues. Data observability can help solve all kinds of common enterprise data issues.
Data observability can help resolve data and analytics platform scaling, optimization, and performance issues, by identifying operational bottlenecks. Data observability can help avoid cost and resource overruns, by providing operational visibility, guardrails, and proactive alerts. And data observability can help prevent data quality and data outages, by monitoring data reliability across pipelines and frequent transformations.