Our project uses Accounts Payable data from an ERP system to predict the payment status of unpaid invoices - specifically whether they will be paid early, late, or on-time. This data in moved through a "medallion" lakehouse architecture and modeled in various notebooks. The results of the predictive model are presented alongside traditional AP reporting in Power BI. Additionally, we generated our calendar table and semantic model descriptions using Copilot. This project is designed to fulfill a real-world need and will be further developed into a production-ready solution for our organization. Thanks for considering our submission!
Project name
Accounts Payable Payment Prediction
Description
Our project uses Accounts Payable data from an ERP system to predict the payment status of unpaid invoices - specifically whether they will be paid early, late, or on-time. This data in moved through a "medallion" lakehouse architecture and modeled in various notebooks. The results of the predictive model are presented alongside traditional AP reporting in Power BI. Additionally, we generated our calendar table and semantic model descriptions using Copilot. This project is designed to fulfill a real-world need and will be further developed into a production-ready solution for our organization. Thanks for considering our submission!
Project Repository URL
https://github.com/aboerger/Fabric-Hackathon-AP-Payment-Prediction
Project video
https://youtu.be/RI7mAwF30wY
Team members
aboerger, rbuttric, MBehne