{"type":"video","version":"1.0","html":"<iframe src=\"https://www.loom.com/embed/329cd49c5e914901bd4c141967dabe87\" frameborder=\"0\" width=\"1920\" height=\"1440\" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>","height":1440,"width":1920,"provider_name":"Loom","provider_url":"https://www.loom.com","thumbnail_height":1440,"thumbnail_width":1920,"thumbnail_url":"https://cdn.loom.com/sessions/thumbnails/329cd49c5e914901bd4c141967dabe87-a4d240e031b3b204.gif","duration":235.694,"title":"A.I. Ops Analytics Demo: Day Three Overview","description":"In this video, I demonstrate a minimal repeatable setup for A.I. ops analytics that allows for quick operational calls. I load CSV data into SQL and visualize it in Metabase, providing insights into average incident resolution times and daily latency. The key metrics include an average of 19 minutes for incident resolution on October 13, 2025, and a focus on understanding customer impact. I emphasize the importance of a metric dictionary to avoid confusion and ensure clarity across the team. No specific action is requested from viewers, but I encourage everyone to explore this setup for their operational needs."}