A portfolio-ready demonstration of the end-to-end data lifecycle — from raw data ingestion to actionable business insights — using a modern Medallion Architecture.
This project highlights data engineering, warehousing, and analytics best practices while remaining easy to understand, reproduce, and extend.
This project adopts the Medallion Architecture to deliver a scalable, maintainable, and quality-focused data flow.
| Layer | Description |
|---|---|
| Bronze | Raw data ingested as-is from ERP & CRM CSV files into SQL Server — acts as the single source of truth. |
| Silver | Cleansed and standardized data, ensuring consistent formatting and integrity. |
| Gold | Business-ready, aggregated data modeled in a star schema optimized for analytics & reporting. |
- Data Architecture — Robust Bronze → Silver → Gold warehouse design.
- ETL Pipelines — Automated CSV ingestion and transformation in SQL Server.
- Data Modeling — Fact & dimension tables following BI best practices.
- Analytics & Reporting — SQL-based insights on customers, products, and sales KPIs.
✅ Data Engineers showcasing SQL & warehouse design skills
✅ Data Analysts building structured datasets for BI
✅ Students & professionals creating portfolio-ready projects
Data Sources:
- ERP System (Products, Sales) — CSV export
- CRM System (Customers) — CSV export
Tech Stack:
- Microsoft SQL Server
- T-SQL for ETL, transformations, and reporting
- Star schema modeling principles
Objectives:
- Consolidate sales & customer data in a SQL Server warehouse
- Cleanse and validate source data for quality
- Integrate sources into a unified, query-optimized model
- Build analytics queries to deliver actionable insights
Prerequisites
- SQL Server installed locally or on a server
- Basic knowledge of T-SQL
- ERP & CRM CSV files
MIT — see the LICENSE file.
I’m Daniel Toluwani Adeleke, a Data Scientist & IT professional with a passion for building end-to-end data solutions. I hold a BSc in Computer Science and an MSc in Data Science & Business Analytics. My expertise includes SQL, Python, Machine Learning, and BI reporting.
📧 Email: dannydave1000@gmail.com 💼 LinkedIn: linkedin.com/in/dannydave 🌐 Portfolio: dannydave.my_portfolio.github.io