E-commerce Performance & Customer Behavior Analytics Deep Dive

Author: Benoit Albert

Status: Draft

Duration: 1 Week Deep Dive

Executive Summary

This intensive project focuses on dissecting a mock e-commerce dataset to uncover critical sales trends, customer purchasing patterns, and operational inefficiencies. Leveraging SQL for data extraction, Python for advanced statistical analysis and cleaning, and Tableau/Power BI for interactive visualizations, the objective is to generate actionable business intelligence.

Key Skills

Project Execution Log

Stage 1: Project Definition & Data Acquisition Strategy

Deliverables

Stage 2: Database Design & SQL Data Extraction/Transformation

Deliverables

Stage 3: Advanced Data Cleaning & Exploratory Analysis with Python/R

Deliverables

Stage 4: Interactive Dashboard Creation with Tableau/Power BI

This stage focused on transforming raw data insights into an accessible, interactive visual narrative. By leveraging Tableau or Power BI, an interactive dashboard was created, emphasizing critical e-commerce KPIs and customer behavior patterns. This not only showcased skills in data visualization and storytelling but also delivered a practical tool for business stakeholders, bridging the gap between complex analysis and actionable business intelligence.

Deliverables

  • [x] The final interactive dashboard file (e.g., `.twbx` for Tableau, `.pbix` for Power BI) containing all visualizations, data connections, and interactive elements.

Stage 5: Business Insights & Strategic Recommendation Development

Deliverables