Airline Company Data Warehouse Project

Overview

This repository contains all the necessary documentation and code for the Data Warehouse project designed for a major airline company. The project aims to enable the executive management to analyze current business processes and identify new opportunities through a structured Data Warehouse that consolidates data from various sources. This enables efficient analytical reporting and business intelligence for improving service delivery and expanding the company's market reach.

Project Team

• Mohamed AlGhaly
• Salma Ahmed
• Ahmed Ali

Project Milestones

• Data Wareouse Model (7 Business Processes Modeled on 2 Deliverables)
• PowerBI Dashboard Build on top of the DWH Model

Documentation

Detailed project documentation is available in the AirLine Company DWH Project.pdf, which outlines the steps taken from business understanding to data analysis and dashboard building.

Features

The Data Warehouse incorporates several key features:

• Ticketing Transactions: Analyzes sales performance, customer booking behaviors, and revenue management.
• Frequent Flyers: Tracking flyer behaviors and booking patterns for company's frequent flyers.
• Customer Care: Focuses on enhancing customer satisfaction by managing inquiries and feedback.
• Flights: Supports performance analysis and operational planning for flight operations.
• Loyalty Program: Manages the airline's loyalty program over all partnered companies.
• Expenses: Analyzes company's operational Expenses across different business processes.
• Revenue: Analyzes company's revenue over time.

DWH MODEL

First Delivery

Second Delivery

Data Marts (Sample)

Reservations

Customer Care

Installation

To set up the project on your local machine for development and testing purposes, follow these steps:

1. Clone the repository:

   git clone https://github.com/al-ghaly/AirLine-Company-Illmon-Data-Warehouse.git

2. Navigate to the project directory:

   cd AirLine-Company-Illmon-Data-Warehouse

Usage

The project uses Oracle DBMS. Ensure you have Oracle installed and configured on your system. Here are the steps to import the project and run it:

1. Execute the SQL scripts found in the Schema Creation.SQL to set up the database schema.
2. Use the Populate.PY script to generate sample data.
3. Populate the data into your database using the scripts in the Data Population folder.
4. Utilize SQL queries or BI tools to analyze the data.