SQL-DATA-WAREHOUSE

Welcome to the Data Warehouse and analytics project Repository!🚀 This project demonstrates how to design and build a modern data warehouse using SQL Server, complete with automated ETL processes, optimized data models, and analytics-ready structures. The goal is to create a scalable, reliable system that transforms raw operational data into meaningful insights for reporting and decision-making.

🚀 Project Requirements

Building the Data Warehouse (Data Engineering)

Objective

To develop a modern data warehouse using SQL Server to consolidate sales data for analytics and decision-making.

Specifications:

• Data Sources: Import CSV files from ERP and CRM systems.
• Data Quality: Cleanse and resolve data quality issues before analysis.
• Integration: Combine both data sources into a single, user-friendly data model for analytical queries.
• Scope: Focus on the latest dataset only; historical data is not required.
• Documentation: Provide clear documentation of the data model for business and analytics stakeholders.

BI: Analytics & Reporting (Data Analytics)

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 — MIT

This project is released under the MIT Licence, a permissive open-source license that allows anyone to use the code for personal, academic, or commercial purposes All you need to do is include the original copyright notice.

👤 About Me

Hi there, I’m Obinna Agunanna - a Data Analyst, Registered Nurse, and Tech Creator who specializes in Creating educational tech content via Technurse Hub. I’m passionate about using data, technology, and innovation to improve healthcare systems and create meaningful digital solutions.

Built With

• sql
• tsql