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Retail Sales Analysis SQL project demonstrating data cleaning, EDA, and business insights. Built a p1_retail_db database, cleaned raw data, ran SQL queries to analyze sales trends, customer behavior, and product performance, and generated reports to support data-driven retail decisions.

A comprehensive SQL project focused on retail sales data analysis, featuring database setup, data cleaning, exploratory analysis, and insightful business-driven queries to uncover sales trends and customer behavior.

This SQL project analyzes a retail sales dataset by performing data cleaning, exploration, and business problem-solving. Queries include sales trends, top customers, category insights, monthly performance, and shift-wise order analysis. Built in MySQL for data-driven decision-making.

This repository features the Retail sales and customer insights dashboard demonstrating data cleaning and analysis using Excel, Python, and SQL, along with interactive visualization in Power BI. Explore the code and reports to gain insights into sales performance, customer behavior, and product trends. A complete end-to-end data analytics workflow

Retail Sales Data Analysis using SQL Server | Data Cleaning, Aggregation, and Business Insights.

Retail Sales Analysis using SQL – Data cleaning, exploration, and business insights generated from transactional sales data.

retial_sales anlaysis using sql, this project includes data cleaning, analysis, and insights on retail sales performances.

End-to-end retail sales analysis: SQL data cleaning, Python automation, and interactive Chart.js dashboard

SQL project showcasing data cleaning, exploratory data analysis, and business insights using a retail sales dataset. Includes SQL scripts for setup, analysis, and performance evaluation.

This project focuses on Retail Store Sales Analysis using SQL, applying EDA and data cleaning techniques directly within SQL to extract meaningful business insights from transactional retail data.

📊 Retail Sales Analysis with SQL – Analyze retail data using SQL to uncover insights on sales, customers, products, and inventory. Includes data cleaning, trend analysis, and segmentation. Works with PostgreSQL/MySQL/SQLite. BI-ready for tools like Power BI/Tableau.

A SQL-based retail sales analysis project featuring database setup, data cleaning, exploration, and business insights through queries on customer behavior, sales trends, and category performance.

Welcome to the **Retail Sales SQL Analysis Project**, where we dive deep into a structured retail database using SQL for data exploration, cleaning, advanced joins, and executive-level business insights.

Coffee Shop Sales Analysis using SQL for querying and Excel for CSV conversion. Includes data cleaning, KPI extraction, and sales trend insights. Built to demonstrate SQL proficiency and business intelligence for retail analytics.

Retail Sales Analysis project using SQL to perform data cleaning, exploratory data analysis (EDA), and business insights generation. Includes queries for sales trends, customer behavior, top customers, and category performance, demonstrating strong SQL, aggregation, and analytical problem-solving skills.

Retail Analytics Case Study using SQL Analyzed retail sales, customer segmentation, and behavior using SQL. Identified high/low-selling products, categorized customers, and tracked loyalty trends to optimize inventory and marketing strategies. Data cleaning and trend analysis helped drive data-driven retail decisions.

Analyzed retail sales data using Python and SQL to extract insights. Performed data cleaning, trend analysis, and visualized KPIs using Pandas, Matplotlib, and Seaborn. Helped identify top products, regions, and monthly sales trends.

This project showcases essential SQL skills for data analysts, focusing on exploring, cleaning, and analyzing retail sales data. Starting with setting up a structured retail sales database, it moves through exploratory data analysis (EDA) and dives into answering key business questions with targeted SQL queries.

End-to-end data analysis of UK Retail Sales (1988–2025) using Python, SQL, and Power BI — featuring data cleaning, forecasting, and a professional dashboard built from ONS data.

Retail sales data analysis using Python, SQL, and Excel to clean, analyze, and visualize data through reports and dashboards. The project focuses on identifying sales trends and generating interactive dashboards, build reports, and visualize retail performance trends."

A SQL-based data analysis project focused on retail sales. It covers database setup, data cleaning, exploratory data analysis (EDA), and business insights using SQL queries. Designed to showcase practical SQL skills in data preparation, querying, and analysis—ideal for beginners building a strong foundation in data analytics.

End-to-end sales analytics project using Python, SQL, and Power BI. Includes data cleaning, exploratory analysis, interactive dashboards, and data-driven business recommendations based on a retail superstore dataset.

This project is designed to demonstrate SQL skills and techniques typically used by data analysts to explore, clean, and analyze retail sales data. The project involves setting up a retail sales database, performing exploratory data analysis (EDA), and answering specific business questions through SQL queries.

This project is designed to demonstrate SQL skills and techniques typically used by data analysts to explore, clean, and analyze retail sales data. The project involves setting up a retail sales database, performing exploratory data analysis (EDA), and answering specific business questions through SQL queries.

This project is designed to demonstrate SQL skills and techniques typically used by data analysts to explore, clean, and analyze retail sales data. The project involves setting up a retail sales database, performing exploratory data analysis (EDA), and answering specific business questions through SQL queries.

This project is designed to demonstrate SQL skills and techniques typically used by data analysts to explore, clean, and analyze retail sales data. The project involves setting up a retail sales database, performing exploratory data analysis (EDA), and answering specific business questions through SQL queries.

This project is designed to demonstrate SQL skills and techniques typically used by data analysts to explore, clean, and analyze retail sales data. The project involves setting up a retail sales database, performing exploratory data analysis (EDA), and answering specific business questions through SQL queries.

This project is designed to demonstrate SQL skills and techniques typically used by data analysts to explore, clean, and analyze retail sales data. The project involves setting up a retail sales database, performing exploratory data analysis (EDA), and answering specific business questions through SQL queries.

End to end Retail sales analysis project using python(pandas,numpy,matplotlib),PostgreSQL , and Power BI ,Includes data cleaning , SQL analysis with 20+ business queries , and an interactive 3-page dashboard