SQL Data Warehouse Project (Data Engineering)

This project demonstrates a complete data pipeline using SQL, including Data Warehousing, ETL/ELT processes, Exploratory Data Analysis, and Advanced Analytics to support business decision-making.

Part 1: Data Engineering — Building the Data Warehouse

Objective

Develop a modern data warehouse to centralize data from ERP and CRM systems, supporting reporting and analysis.

Specifications

• Data Sources: Import data from two source systems (ERP and CRM), provided as CSV files.
• Data Quality: Cleanse and resolve data quality issues before performing analysis.
• Integration: Merge both sources into a single, user-friendly data model optimized for analytical queries.
• Scope: Focus on the most recent dataset (historical data is not required).
• Documentation: Provide comprehensive documentation to support both business users and analytics teams.

Part 2: Data Analytics — BI, Reporting & Insights

Objective

Develop SQL-based analytics to deliver actionable insights into:

• Customer Behavior
• Product Performance
• Sales Trends

📄 License

This project is licensed under the MIT License. You are free to use, modify, and share this project.

📝 Note

• 🚧 This project is currently in progress, and the repository is being updated step by step.
• 🗂️ Project planning and progress tracking are available on Notion.
• 📌 Check the steps of the project file in the repository to get more information about the development phases and tasks.