Building a modern data warehouse with SQL Server, including ETL process, data modeling and analytics.
Welcome to the Datawarehouse and Analytics Project repository! This project demonstrates the end-to-end implementation of a modern data warehouse solution using SQL Server. It covers the complete data engineering lifecycle — from raw data ingestion to building analytical-ready data models.
The solution follows a layered architecture approach (Bronze, Silver, Gold) to ensure data quality, scalability, and performance optimization.
🔹 Project Highlights
- Designing a structured Data Warehouse architecture
- Implementing ETL pipelines using SQL
- Data cleansing and transformation processes
- Building Fact and Dimension tables (Star Schema)
- Creating analytical queries for business insights
- Applying best practices in indexing, constraints, and performance tuning
🏗️ Architecture Overview Bronze Layer → Raw data ingestion Silver Layer → Cleaned and transformed data Gold Layer → Business-ready analytical data models