Mohamed-Abdelaaty/Enterprise-BI-Solution-for-Digital-Egypt-Pioneers-Initiative-DEPI-
Domaine:
socioeconomicCréateur:
Moh
Hôte:
Enterprise BI solution: PostgreSQL QC pipeline, Power BI model & DAX measures for DEBI Round 5 training program.
🇪🇬 Enterprise BI Solution for Digital Egypt Pioneers Initiative (DEPI)
An end-to-end Business Intelligence solution for DEBI Round 5 — from raw PostgreSQL data,
through automated daily quality checks, to a full Power BI semantic model and report.
---
## 📖 Overview
**DEPI_R5_Report** gives the Digital Egypt Builders Initiative (DEBI)
Round 5 program team the operational insight needed to manage and improve training delivery —
covering trainees, training providers (TPs), groups, instructors, halls, and sessions — so the
client can make timely decisions on session planning, quality, and trainee outcomes.
| | |
|---|---|
| **Initiative** | Digital Egypt Builders Initiative (DEBI), Ministry of Communications and Information Technology (MCIT) |
| **Vendor** | WAVZ For Digital Transformation |
| **Role** | BI Engineer — end-to-end solution design, data modeling, DAX, and report authoring |
| **Source system** | PostgreSQL |
| **BI platform** | Power BI Desktop — PBIP/PBIR project format, TMDL semantic model definitions |
This repo documents the full solution: the data-quality layer in SQL, the automated daily
QC-and-email pipeline in Python, the star-schema semantic model, the DAX measure library, and
the Power BI report itself.
---
## 🎯 Objectives & Scope
The client requested a single report delivering insight across six subject areas:
- **Trainees** — demographics, attendance, performance
- **Training Providers (TPs)** — delivery volume and quality
- **Groups** — round/group-level tracking and target progress
- **Instructors** — assignment and performance *(on hold — see Known Gaps)*
- **Halls** — physical-session capacity and quality
- **Sessions** — planned vs. conducted vs. non-conducted, online and physical
---
## 🏗️ Architecture
```
PostgreSQL (source)
│
├── 7 daily QC views ──────► qc_pipeline.py ──────► CSV exports + Outlook email
│ (daily automated data quality report)
│
└── Fact …