{"type":"video","version":"1.0","html":"<iframe src=\"https://www.loom.com/embed/c971bf84f0e047f28b1826c092d2b4f1\" frameborder=\"0\" width=\"1660\" height=\"1245\" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>","height":1245,"width":1660,"provider_name":"Loom","provider_url":"https://www.loom.com","thumbnail_height":1245,"thumbnail_width":1660,"thumbnail_url":"https://cdn.loom.com/sessions/thumbnails/c971bf84f0e047f28b1826c092d2b4f1-4e59ac426169ac7f.gif","duration":1179.891,"title":"Automating Data Migration Readiness Assessment with Snowflake","description":"Hi, I'm Sharmila Bogadi, a data engineer specializing in healthcare analytics. In this video, I present my project called Migration Readiness Scorer, a tool that automates the assessment of whether a client's data is ready for migration to Snowflake. I used real data from the CMS Medicare inpatient dataset, consisting of 146,427 records, to demonstrate how my tool provides insights on data quality across four dimensions: completeness, uniqueness, consistency, and governance. The overall readiness score achieved is 92.50 out of 100, with minor issues identified. I encourage you to check out my GitHub repository for detailed documentation and SQL scripts related to this project."}