Automated Root Cause Analysis with Claude

Automated root-cause analytics is becoming one of the most important capabilities for modern data teams — especially when AI agents and orchestration platforms are involved. In this video, we walk through how to use Claude alongside Orchestra to automatically triage failed data pipelines. You’ll see how pipeline metadata, lineage, logs, task dependencies, and observability signals can be combined with Claude Code to identify the true source of pipeline failures in seconds instead of hours. We’ll go through a practical example common to every data engineer, pulling on the thread of "This dashboard looks off". You’ll learn how Claude analyzes logs, lineage, and code changes to isolate problematic areas of the pipeline. Claude will also generate code fixes, autonomously tested via pipeline re-runs through Orchestra. This is especially useful for analytics engineers, platform engineers, AI engineers, and modern data teams building agentic workflows and AI-powered data platforms. Additional resources: Website: https://getorchestra.io Sign up: https://app.getorchestra.io Documentation: https://docs.getorchestra.io #dataengineering #claudecode #aiengineering #datapipelines #claude #analyticsengineering #dataops #datapipeline #rootcauseanalysis #aiworkflow #dataplatform #orchestration