In this personal Superstore Sales SQL Data Analysis project, an exploratory data analysis was performed on the Superstore Sales Data available on Kaggle. The main aim of the project is to uncover insights into the store's sales and profits trends and patterns from 2014 to 2017.

This repository features the Superstore Sales Analysis project, demonstrating data cleaning and analysis using 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 analysis.

End-to-end retail sales data cleaning, analysis & forecasting using Python, SQL & Tableau. Analyze & forecast retail sales using Global Superstore data: Python (Pandas, Matplotlib), SQLite, Tableau dashboards. Keep it under 100 characters if possible so it displays well.

An Analytical look into a Superstore data using Time Series Analysis approach with SQL windows functions.

This project analyses the Global Superstore dataset to uncover insights into sales, profit, customer segments, and shipping methods. The analysis was done using SQL for querying and Power BI for visualization.

SQL analysis on Sample Superstore (SQLite)

Superstore Sales Analysis Using SQL (MySQL Workbench)

End-to-End data analysis of Superstore dataset using SQL

Superstore Sales SQL Analysis project using multiple tables including customers, orders, products, and location. Implemented filtering, joins, aggregations, window functions, and ranking to analyze sales, profit, top products, regional performance, and customer insights.

Superstore Sales Data Analysis with SQL

SQL project to analyze super store data. The focus of this project is to learn to write different SQL queries to create and insert data into the database and to retrieve data from the database to analyse superstore sale. By answering the different types of questions, we tried to help the store understand its business growth

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Comprehensive sales, churn, and customer risk analysis using SQL and Power BI.

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SQL analysis of Global Superstore USA data validated with Power BI

An SQL-based analysis of the Superstore dataset to identify key drivers of sales and profitability.

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End-to-end sales, profitability, and operations analysis using MySQL and Python

Analyzed US Superstore dataset using SQL & Power BI to uncover sales trends, profit drivers, and regional performance. Built an interactive dashboard with KPIs, YoY growth, and product-level insights.

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SQL-based revenue leakage analysis using Superstore data

SQL-Project

This Power BI Dashboard provides a 360° view of sales and profitability performance for the Superstore.

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This repository features the Superstore Sales Analysis project, demonstrating data cleaning and analysis using 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 analysis.

SQL and Tableau project on the sales analysis of a global superstore

Exploratory Data Analysis (EDA) of Superstore dataset using Python. SQL analysis and dashboard visualization coming next.