{"type":"video","version":"1.0","html":"<iframe src=\"https://www.loom.com/embed/a0d9992abf5b44fb8904a30d94a3346a\" frameborder=\"0\" width=\"1728\" height=\"1296\" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>","height":1296,"width":1728,"provider_name":"Loom","provider_url":"https://www.loom.com","thumbnail_height":1296,"thumbnail_width":1728,"thumbnail_url":"https://cdn.loom.com/sessions/thumbnails/a0d9992abf5b44fb8904a30d94a3346a-672dca130810c3e3.gif","duration":224.738,"title":"Optimizing Data Scraping and Ranking for Insights 🚀","description":"In this video, I walk you through my current project involving a template that scrapes names from a webpage and ranks individuals based on their seniority. The process is a bit slow, taking about a minute for 60 people, and I’m looking for ways to improve that for larger datasets. I also encountered a limitation where it only retrieves the first 100 records from a company, and I'm considering a workaround to address this. If you're interested, I can share my formulas and the worksheet with you. Please let me know if you’d like to see it!"}