Amazon Sales Analytics – Power BI and Python
Nitu Alam
Amazon_Sales_Analysis
Have to conduct a detailed year-wise analysis of Amazon sales data to understand sales trends by identifying key metrics and other factors and show the meaningful relationship between attributes.
𝗜𝗻𝘀𝗶𝗴𝗵𝘁𝘀:
⦿ Top 5 Gross Profit Margin Categories:
Cosmetics, Households, Office Supplies, Clothes, and Baby Food are the top-performing categories in terms of gross profit margin.
⦿ Profit Percentage by Sales Channels:
Online sales contribute to 44% of the total profit, while offline sales contribute to the remaining 56%
⦿ Profit Percentage by Customer Preferences:
High-priority customer preferences generate 38% of the total profit, followed by the least priority (25%), medium (22%), and cancels (15%).
⦿ Monthly Trends:
February, July, and November exhibit the highest number of orders, while March, June, and August show the Lowest order volumes.
⦿ Profit Percentage by Regions:
Europe and Sub-Saharan Africa are the most profitable regions, contributing 25% and 28% respectively to the total profit. Other significant regions include Asia (14%), Australia and Oceania (11%), Central America and the Caribbean (6%), and Middle East & North America (13%).
⦿ Most Profitable Countries:
Djibouti and Myanmar emerge as the most profitable countries within the regions analyzed.
𝗧𝗼𝗼𝗹𝘀 𝗮𝗻𝗱 𝗧𝗲𝗰𝗵𝗻𝗼𝗹𝗼𝗴𝗶𝗲𝘀:
Python
PowerBI
Canva
𝗣𝗿𝗲𝘀𝗲𝗻𝘁𝗮𝘁𝗶𝗼𝗻 𝗟𝗶𝗻𝗸: https://rb.gy/tjhgua
𝗗𝗮𝘀𝗵𝗯𝗼𝗮𝗿𝗱 𝗟𝗶𝗻𝗸: https://project.novypro.com/myWUP2
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Posted Sep 13, 2026
Analyzed Amazon sales data using Python and Power BI to clean records, identify trends, compare product performance and build an interactive dashboard.
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Timeline
Feb 10, 2025 - Feb 15, 2025
Clients
Amazon
