{"id":26685177,"url":"https://github.com/coderbiswajit24/walmart-sales-analysis-comprehensive-sql-based-data-insights","last_synced_at":"2026-02-04T23:41:07.216Z","repository":{"id":272139681,"uuid":"915636210","full_name":"Coderbiswajit24/Walmart-Sales-Analysis-Comprehensive-SQL-Based-Data-Insights","owner":"Coderbiswajit24","description":"A comprehensive SQL analysis of Walmart's sales data, exploring sales patterns, store performance, and promotional impacts. 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This project leverages SQL queries to extract actionable insights from retail data, helping understand seasonal trends and regional variations in sales performance.\n\n![image_alt](https://github.com/Coderbiswajit24/Walmart-Sales-Analysis-Comprehensive-SQL-Based-Data-Insights/blob/19bfc168b401e5697e6eea8df24bf4090b6581fd/Walmart_image.jpg)\n\n## Project Objectives\n\n### Sales Performance Analysis\n- **Identify top-performing branches, cities, and product lines.**\n- **Classify product lines as \"Good\" or \"Bad\" based on sales performance.**\n- **Analyze branch-wise total sales and monthly revenue trends.**\n\n### Customer Behavior Insights\n- **Understand customer preferences by gender, city, and customer type.**\n- **Determine the most common product lines and payment methods.**\n- **Analyze customer gender distribution and satisfaction ratings.**\n\n### Revenue and Tax Analysis\n- **Identify the top revenue-generating cities, branches, and customer types.**\n- **Analyze trends in gross margin percentage and tax/VAT contributions.**\n\n### Time-Based Trends\n- **Study sales trends by time of day, weekday, and month.**\n- **Determine the best average ratings by branch and weekday.**\n\n### Customer Satisfaction\n- **Evaluate customer satisfaction ratings by payment method, branch, and time of day.**\n- **Identify factors contributing to high customer satisfaction.**\n\n## Project Overview\n\nThis project involves a comprehensive analysis of Walmart's sales data to uncover actionable insights. The analysis focuses on understanding sales performance, customer behavior, and revenue trends. Key areas of exploration include:\n\n### Product Line Analysis\n- **Identifying best-selling product lines and their performance across different customer demographics.**\n\n### Branch and City Performance\n- **Evaluating the sales and revenue contributions of various branches and cities.**\n\n### Customer Insights\n- **Analyzing customer preferences, satisfaction ratings, and gender distribution.**\n\n### Time-Based Trends\n- **Understanding how sales and customer satisfaction vary by time of day, weekday, and month.**\n\n### Revenue and Taxation\n- **Identifying top revenue-generating entities and analyzing tax contributions.**\n\nThe insights derived from this analysis will help Walmart optimize its operations, improve customer satisfaction, and enhance overall business performance.\n\n## Thank You!\n\n![Thank You](https://th.bing.com/th/id/OIP.lsrYKH1UItL1uVP4kTv1ZQHaHa?pid=ImgDet\u0026w=474\u0026h=474\u0026rs=1)\n\nThank you for visiting and supporting my project!\n\n\nIf you'd like to refine this further or need additional details, let me know!\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcoderbiswajit24%2Fwalmart-sales-analysis-comprehensive-sql-based-data-insights","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fcoderbiswajit24%2Fwalmart-sales-analysis-comprehensive-sql-based-data-insights","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcoderbiswajit24%2Fwalmart-sales-analysis-comprehensive-sql-based-data-insights/lists"}