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End-to-End Supply Chain Analytics Project
End-to-end analytics workflow covering supply chain optimization, demand forecasting, and operational insights
Role
Data Analyst
Duration
2 weeks
Tech Stack
Python, SQL, Pandas, Power BI, MySQL, DAX
Project Overview
Developed an end-to-end Supply Chain Analytics solution by transforming a raw dataset of 180,519 records and 53 features into actionable business insights using Python, MySQL, and Power BI. The project followed the complete analytics lifecycle, including data cleaning, SQL-based business analysis, interactive dashboard development, and business recommendations to support data-driven decision-making.
Key Features
- ✓Cleaned and preprocessed raw supply chain data using Python (Pandas).
- ✓Identified and handled missing values while validating data quality.
- ✓Verified that the dataset contained no duplicate records.
- ✓Designed and executed SQL queries to analyze:
- ✓Delivery Status
- ✓Late Delivery Risk by Market
- ✓Top Product Categories by Sales
- ✓Shipping Mode Distribution
- ✓Developed an interactive Power BI dashboard featuring KPIs, category analysis, shipping insights, and market-level performance.
- ✓Generated business insights and strategic recommendations to improve supply chain operations and decision-making.
Technologies Used
PythonSQLPandasPower BIMySQLDAX