{"type":"video","version":"1.0","html":"<iframe src=\"https://www.loom.com/embed/baf6339fef164d1ab63c5569d411046b\" frameborder=\"0\" width=\"1152\" height=\"864\" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>","height":864,"width":1152,"provider_name":"Loom","provider_url":"https://www.loom.com","thumbnail_height":864,"thumbnail_width":1152,"thumbnail_url":"https://cdn.loom.com/sessions/thumbnails/baf6339fef164d1ab63c5569d411046b-00001.gif","duration":262.143,"title":"Big Data Challenge Solution","description":"In this video, we present our solution to the Big Data Challenge organized by FS. We address the issue of predicting retail shop orders by introducing a future where FS representatives know exactly what they need before they believe they chose. We discuss the four main pillars of our solution: description, custom rate, data analysis, and bonding with store owners. We also explain the three main challenges we faced: the data language challenge, the algorithm challenge, and the usability challenge. Our solution includes a user-friendly dashboard tailored for FS representatives, offering clarity and forecasted value graphs. We highlight our competitive advantages and revenue model. Watch the video to learn more!"}