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⬇️ Click below to book a call ⬇️ https://dataengineeracademy.com/ytinvite ⬇️ Click below to explore our coursework ⬇️ https://dataengineeracademy.com/ytcou... If you’re new to my channel, my name is Christopher Garzon. I run the top Data Engineering Academy in the country, where we help students transition into data engineering from other data professions to increase their compensation. How I got here… At 18 years old, I started at Boston College. At 20, I was sneaking into graduate-level classes to take machine learning and data science courses. At 21, I invested in a data science course from a mentor and wired him $3,000 without ever meeting him. At 22, I landed my first job as a data analyst at Amazon, making $60,000 per year. At 24, I became a data engineer at Amazon, increasing my salary to $100,000 and started angel investing in a couple of data companies. At 25, I moved to a startup as a data engineer and doubled my income to $200,000 per year. At 26, I was making about $350,000 at Lyft. At 27, Lyft stocks went up, and my total compensation reached around $450,000. That same year, I launched the Data Engineering Academy. For the last two and a half years, I’ve been running the Data Engineering Academy full-time, helping thousands of people transition into data engineering and significantly increase their earning potential. To all the data professionals grinding—your journey is still being written. The bigger the obstacles, the greater the story. Remember, don’t settle for your next job. Go for a better one. Chris 00:00:00 - Snowflake Overview: 00:09:17 - Snowflake Editions: 00:13:25 - Snowflake Architecture: 00:28:00- Snowflake Account Setup: 00:32:08- Snowflake UI overview: 00:41:12- Snowflake Users Roles: 00:46:24- Snowflake Database Schema: 00:55:32- Snowflake Table Types: 01:08:26 - Snowflake View Types: 01:21:01 - Snowflake Stages: 01:37:10 - Snowflake File Formats: 01:48:29 - Snowflake Data Loading Approaches: 01:59:46 - Snowflake Bulk Data Load: 02:16:02 - Snowflake Continuous Data Load: 02:40:12 - Snowflake Streams: 03:01:29 - Snowflake Tasks: 03:17:29 - Snowflake Time Travel And Fail Safe: 03:42:44 - Snowflake Cloning