Adidas required a robust system to monitor and optimize key business metrics including Average Order Value (AOV), Customer Acquisition Cost (CAC), Total Sales, and Total Profit.
Tech Stack & Implementation
The project required a multi-step data engineering approach to ensure accuracy:
- Data Cleaning (Python): Processed raw datasets using Pandas to handle inconsistencies and missing values, ensuring data integrity.
- Database Storage (SQLite3): Pushed cleaned data into a structured SQLite database for high-performance querying and manipulation.
- Advanced SQL: Designed complex queries to calculate live AOV and CAC metrics directly from the data warehouse.
- PowerBI Visualization: Developed an enterprise-grade dashboard with interactive KPIs and intuitive layouts for executive decision-making.
Outcomes
The resulting system enabled Adidas stakeholders to:
- Monitor Real-Time KPIs: Clear visibility into order value trends and acquisition costs.
- Strategic Decision Making: Data-driven insights into profit margins across different product lines.
- Process Optimization: Streamlined the flow of data from raw assets to boardroom-ready visualizations.