Accounts Receivable Analytics
An accounts-receivable analytics scenario connecting synthetic transactions, Power Query transformations, and a star schema.
A question. A process.
Work you can explore.
Move from the project’s purpose to its available previews and source files.
Chapter 1 of 4 · The question
What this project explores.
An accounts-receivable analytics scenario connecting synthetic transactions, Power Query transformations, and a star schema.
Follow the implementation.
The repository documents Accounts Receivable Analytics. Start with the README and follow its setup and implementation files; the source collection below gives you a way into the work.
Read the implementation notesLook beyond the project summary.
The source files and README are the available evidence for this project. Open them to review the implementation and its assumptions.
Choose where to look deeper.
Search the linked source inventory or narrow it to the kind of artifact you want to inspect. Files open at their original source.
6 linked source files
No linked files match this view.
The source
keeps moving.
Source updated
An end-to-end Accounts Receivable data engineering pipeline — synthetic data generation at scale (950K+ records), Power Query ETL transformation, Star Schema modeling, and collection follow-up simulation — built for real-world AR analytics scenarios.
Current README excerpt
- 🎯 Project Overview - 🏗️ Architecture & Data Flow - 📐 Architecture Diagram - 📁 Repository Structure - 🗄️ Data Model — Star Schema - 📓 Notebooks - 🔧 Scripts — Daily Updates & CDC - ⚙️ ETL Engine - 📊 Power BI Dashboard - 🗓️ Power Query Queries — dim\Date & Dynamic\Holidays - ⚡ Performance - 🚀 Getting Started - 📈 Key Metrics & KPIs - 🔍 Data Lineage - 🤝 Contributing - 📄 License
A source excerpt, not an independently verified outcome.