https://github.com/chandantech2023/sales-trend-analysis

This repository features the Superstore Sales Analysis project, demonstrating data cleaning and analysis using Python and SQL, along with interactive visualization in Power BI. .
https://github.com/chandantech2023/sales-trend-analysis

data-analysis data-science dax kaggle powerbi-desktop python3 sql

Last synced: about 2 months ago
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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. .

• Host: GitHub
• URL: https://github.com/chandantech2023/sales-trend-analysis
• Owner: ChandanTech2023
• Created: 2025-02-23T09:56:21.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2025-02-23T10:49:50.000Z (over 1 year ago)
• Last Synced: 2025-10-09T12:36:53.864Z (9 months ago)
• Topics: data-analysis, data-science, dax, kaggle, powerbi-desktop, python3, sql
• Language: Jupyter Notebook
• Homepage:
• Size: 2.52 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
# Sales-Trend-Analysis 🌟

## This project is demonstrating data cleaning and analysis using Python and SQL, along with interactive Power BI Dashboard. 

# Problem Statement 👉

The problem addressed in this project is to analyze the sales data of a superstore and gain valuable insights to drive business decisions. The challenges include cleaning and transforming the raw data, performing exploratory analysis(EDA), and visualizing to findings insights in an intuitive and informative manner.



  

  

  

 


# The repository contains the following components:

  *  Python scripts for data cleaning and transformation of the Excel dataset.

  * SQL dump file for importing the transformed data into a SQL database.

  * SQL queries for performing exploratory analysis and extracting insights from the sales data.

  *  Power BI project file (.pbix) containing the interactive reports with three pages: sales performance, customer analysis, and product analysis.