End-to-End Retail Analytics Dashboard
Developing a 360° business monitoring system from raw multi-table data to interactive executive reporting.
From Raw Tables to Relational Model
Instead of using a pre-cleaned flat file, I simulated a complex retail environment by generating a 6-table relational dataset. The project spanned the entire data lifecycle: cleaning raw inputs, establishing primary/foreign key relationships in a Star Schema, and engineering DAX measures to calculate performance metrics.
SQL & Excel Architecture
I utilized PostgreSQL to practice complex joins and CTEs, ensuring that the disparate tables (Customers, Products, Regions, and Sales) could be unified without losing data integrity.
- Applied Window Functions to rank top customers by total spend.
- Validated data in Excel using conditional formatting to detect outliers.
DAX Financial Logic
"Leveraging my financial background, I created custom DAX measures to translate raw sales data into business-ready KPIs. These measures allow for dynamic calculation regardless of filters applied."
Advanced Visualization Techniques
3-Level Hierarchy Drill
Engineered a bar chart allowing users to drill down from Category to Specific Product, and finally to individual Order IDs, revealing granular performance at every level.
Customer Loyalty Analysis
Developed a 'Days Since Join' tracking system using a calculated column to identify long-term customer trends.
Business Intelligence Impact
"This project demonstrates my ability to take raw, unorganized data and turn it into a strategic asset. By bridging SQL data manipulation with Power BI visualization, I've created a tool that answers both 'What happened?' and 'Why did it happen?'"
Interested in the SQL & Documentation?
The full SQL scripts and Power BI documentation are available on my GitHub.
Explore Repository