<?xml version="1.0" encoding="UTF-8"?><oembed><type>video</type><version>1.0</version><html>&lt;iframe src=&quot;https://www.loom.com/embed/faf82cc118a94b608a19aecc7e66779e&quot; frameborder=&quot;0&quot; width=&quot;1662&quot; height=&quot;1246&quot; webkitallowfullscreen mozallowfullscreen allowfullscreen&gt;&lt;/iframe&gt;</html><height>1246</height><width>1662</width><provider_name>Loom</provider_name><provider_url>https://www.loom.com</provider_url><thumbnail_height>1246</thumbnail_height><thumbnail_width>1662</thumbnail_width><thumbnail_url>https://cdn.loom.com/sessions/thumbnails/faf82cc118a94b608a19aecc7e66779e-43f192aa506944f9.gif</thumbnail_url><duration>157.264</duration><title>Self-Enriching Business Intelligence Database System Explained 📊</title><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.</description></oembed>