This repository presents a structured collection of SQL scripts designed to demonstrate advanced data analysis and reporting capabilities using relational databases. The analyses are performed on data sourced from the gold layer of my PostgreSQL-based Data Warehouse built from scratch (see project here).
The repository showcases a wide range of analytical techniques and use cases commonly encountered in business intelligence and data analytics workflows, including:
- Database schema and data profiling
- Dimensional data exploration
- Time range and temporal trends analysis
- Computation of key business measures and metrics
- Magnitude and volume quantification
- Ranking and top‑N analyses
- Time series change detection
- Cumulative and rolling analytics
- Performance evaluation and KPI tracking
- Segmentation and cohort analysis
- Part‑to‑whole contribution analysis
- Customer‑centric reporting
- Product‑centric reporting
Each script is focused on a specific analytical theme and illustrates best practices for writing clear, efficient, and reusable SQL queries to support decision‑making processes. The repository is intended to serve as a reference for data analysts and BI professionals seeking practical SQL patterns for data exploration, segmentation, and reporting within a relational data model.
The diagram below illustrates the end‑to‑end transformation roadmap followed during the construction of the analytical layer:
This project is licensed under the MIT License. You are free to use, modify, and share this project with proper attribution.
Let's stay in touch! Feel free to connect with me on Linkedin. Hi there ! I am El Hadji Dame Lo KABA IT Engineer / data scientist / machine learning Engineer/ data Engineer.
