This dataset simulates the operations of a major car distribution company in Egypt (similar to Ghabbour or Mansour Automotive).
The company:
Distributes vehicles to dealers across Egyptian governorates.
Operates multiple warehouse hubs.
Tracks wholesale transactions.
Monitors sales representative performance.
Maintains historical inventory snapshots.
The dataset is modeled using a proper Star Schema and contains:
6 Dimension tables
3 Fact tables
Strict referential integrity
Business-driven KPIs (Commission, Consumption, Coverage Days, etc.)
It is ideal for:
Power BI workshops
Data modeling training
DAX practice
Supply chain analytics case studies
Interview preparation
🗂 Tables Included
📊 Dimension Tables
1️⃣ Dim_Date
Time dimension with:
Date_Key
Date
Year
Month
Quarter
Is_Weekend
2️⃣ Dim_Vehicle_Specs
Vehicle product dimension:
Vehicle_Key
Model_Name (Tucson, Sunny, Tipo…)
Brand (Hyundai, Nissan, Fiat…)
Year_Model
Trim_Level
Engine_CC
Transmission_Type
Origin (Local / Imported)
3️⃣ Dim_Dealer_Showroom
Dealer channel dimension:
Dealer_Key
Dealer_Name
Region (Cairo, Alexandria, Delta, Upper Egypt)
City
Dealer_Grade (A, B, C)
4️⃣ Dim_Warehouse_Hub
Warehouse dimension:
Warehouse_Key
Warehouse_Name (Obour Hub, Abu Rawash Yard…)
Location
Capacity_Units
5️⃣ Dim_Sales_Rep
Sales force dimension:
Sales_Rep_Key
Rep_Name
Gender
Region_Assigned
Hire_Date
Sales_Target_EGP
📈 Fact Tables
1️⃣ Fact_Wholesale_Distribution
Represents wholesale transactions from distributor to dealers.
Columns:
Transaction_ID
Vehicle_Key
Dealer_Key
Warehouse_Key
Date_Key
Quantity
Unit_Price_EGP
Customs_Paid_EGP
Development_Fee_EGP
Total_Invoice_EGP
2️⃣ Fact_Inventory_Snapshot
Historical inventory levels (weekly snapshots).
Columns:
Snapshot_ID
Vehicle_Key
Warehouse_Key
Date_Key
Units_On_Hand
Units_Reserved
Avg_Stock_Age_Days
3️⃣ Fact_Sales_Performance_Stock_Consumption
Sales rep performance and transaction status tracking.
Columns:
Transaction_ID
Sales_Rep_Key
Vehicle_Key
Dealer_Key
Warehouse_Key
Date_Key
Commission_EGP
Sales_Status (Completed / Pending / Cancelled)
🔗 Data Relationships
The dataset follows a clean Star Schema:
Dimensions filter Facts (Single Direction).
No direct Fact-to-Fact relationships are required.
Transaction_ID is used for logical attribution between:
Fact_Wholesale_Distribution
Fact_Sales_Performance_Stock_Consumption
🎯 Use Cases
This dataset supports:
✔ Power BI dashboards
✔ Star Schema modeling practice
✔ DAX advanced functions (CALCULATE, TREATAS, SUMX, DIVIDE)
✔ Supply chain analytics
✔ Performance management
✔ Interview technical tests