{"type":"video","version":"1.0","html":"<iframe src=\"https://www.loom.com/embed/faf82cc118a94b608a19aecc7e66779e\" frameborder=\"0\" width=\"1662\" height=\"1246\" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>","height":1246,"width":1662,"provider_name":"Loom","provider_url":"https://www.loom.com","thumbnail_height":1246,"thumbnail_width":1662,"thumbnail_url":"https://cdn.loom.com/sessions/thumbnails/faf82cc118a94b608a19aecc7e66779e-43f192aa506944f9.gif","duration":157.264,"title":"Self-Enriching Business Intelligence Database System Explained 📊","description":"In this video, I introduce a self-enriching, self-improving database system designed for business intelligence. It answers basic data questions, identifies missing information, and suggests updates to the database structure when necessary. For example, I demonstrate how it can query employee data for Chipotle and handle any gaps by utilizing scraper and schema agents. I encourage you to consider how this system could enhance our data management processes and invite any feedback or questions you may have."}