<?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/2bf3a187edb54c3cae8f32b5430dd0cd&quot; frameborder=&quot;0&quot; width=&quot;1280&quot; height=&quot;960&quot; webkitallowfullscreen mozallowfullscreen allowfullscreen&gt;&lt;/iframe&gt;</html><height>960</height><width>1280</width><provider_name>Loom</provider_name><provider_url>https://www.loom.com</provider_url><thumbnail_height>960</thumbnail_height><thumbnail_width>1280</thumbnail_width><thumbnail_url>https://cdn.loom.com/sessions/thumbnails/2bf3a187edb54c3cae8f32b5430dd0cd-1691776334922.gif</thumbnail_url><duration>1191.93</duration><title>Create and deploy a BigQuery pipeline from scratch</title><description>In this video, I&apos;ll show you how to create and deploy a data pipeline using a combination of tools like DLT, DBT, DugDB, and MotherDug. The best part is that I&apos;ll be doing it all in Python, making it highly customizable for any source or data. With just a few lines of code, you&apos;ll have a fully deployed data pipeline up and running. Get ready to streamline your data processing!</description></oembed>