Data Warehouse and Analytics Project

Welcome to the Data Warehouse and Analytics Project repository! This project demonstrates a comprehensive data warehousing and analytics solution, from building a data warehouse to generating actionable insights. Designed as a portfolio project highlights industry best practices in data engineering and analytics

Project requirements

Building the data warehouse (data engineering)

Objective

Develop a modern data warehouse using SQL Server to consolidate sales data, enabling analytical reporting and informed decision-making

Specifications

• Data sources: Import data from two source systems (ERP & CRM) provided as CSV files.
• Data Quality: Cleanse and resolve data quality issues before analysis.
• Integration: Combine both sources into a single, user-friendly data model designed for analytical queries
• Scope: Focus on the latest dataset only;historization of data is not required.
• Documentation: provide clear documentation of the data model to support both business stakeholders and analytics teams

BI: Analytics & Reporting

Objective

Develop SQL-based analytics to deliver detailed insights into:

• Customer behavior
• Product performance
• Sales trends

These insights empower stakeholders with key business metrics, enabling strategic decision-making

License

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