Welcome to 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
Develop a modern data warehouse using SQL server to consolidate sales data, enabling analytical reporting and informed decision-making.
- Data Sources: Import data from two source system (ERP and CRM) provided as CSV files.
- Data Quality: Cleanse and resolve data quality issues prior to analysis.
- Integration: Combine both sources into a single, user-friendly data model designed for analytical queries.
- Scopes: 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 analytical teams.
Develop SQL-based analytics to deliver detailed insights into:
- Customer Behavior
- Product performance
- Sales Trends
These insights empower stakeholders with key businessmetrics, enabling strategic decision-making
This project is licensed under the MIT License. You are free to use, modify, and share this project with proper attribution
👋 I'm Tejas Nivrutti Divase, a 2nd-year AI & Data Science student at Dr. J.J. Magdum College of Engineering. Passionate about data science and AI, I work with Python, pandas, and ML to solve real-world problems. Also, I create 3D animations on my YouTube, TejXsTuDiOs. 📫 Connect via [https://www.linkedin.com/in/tejas-divase-897996244?utm_source=share&utm_campaign=share_via&utm_content=profile&utm_medium=android_app] for collabs! 🚀