This repository contains the files and a high-level overview of a data analysis project focused on an e-commerce supply chain. The project's goal was to leverage data to identify key performance indicators (KPIs), analyze business trends, and provide strategic recommendations to optimize efficiency and profitability.
Data Generation: Python script used to create a synthetic dataset
Data Analysis: Key insights on revenue, shipping performance, and geographical trends
Final Report: A detailed Google Doc outlining the full methodology, analysis, and recommendations
Interactive Dashboard: A live, dynamic dashboard for exploring the data
Python: For data generation.
Google Sheets: For data cleansing and preparation. Dataset plus Pivot tables: [https://docs.google.com/spreadsheets/d/1Dc7LYO9lNTDC9sxXzJ1M33rUvge4cICQ2Pbxeh1uFW8/edit?usp=sharing]
Tableau: For data visualization and dashboard creation.
For a complete breakdown of the project, including the problem statement, methodology, detailed findings, and business recommendations, please refer to the Google Doc below.
Detailed Project Report: [https://docs.google.com/document/d/1ZunVCN7EcEMVK-BhZEWmX_cammvjoZWron3lveasxuM/edit?usp=sharing]
To interact with the live dashboard and explore the data visualizations, click on the link to the Tableau Public dashboard.
Interactive Dashboard: [https://public.tableau.com/app/profile/aklilu.abera/viz/GlobalLinkLogisticsDataAnalysisProject/Dashboard1]