https://github.com/sushantoroy-stat/road_accident_analysis

This repository showcases a comprehensive analysis of a road accident dataset using SQL, Python, and Power BI. The goal of this project was to uncover insights and visualize patterns to support data-driven decision-making.
https://github.com/sushantoroy-stat/road_accident_analysis

powerbi python sql

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This repository showcases a comprehensive analysis of a road accident dataset using SQL, Python, and Power BI. The goal of this project was to uncover insights and visualize patterns to support data-driven decision-making.

• Host: GitHub
• URL: https://github.com/sushantoroy-stat/road_accident_analysis
• Owner: sushantoroy-stat
• Created: 2024-12-02T14:31:44.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2025-01-24T04:21:29.000Z (over 1 year ago)
• Last Synced: 2025-09-22T09:11:40.725Z (9 months ago)
• Topics: powerbi, python, sql
• Language: Jupyter Notebook
• Homepage:
• Size: 12.4 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
# road_accident_analysis

#🚦 Road Accident Data Analysis

This repository showcases a comprehensive analysis of a road accident dataset using SQL, Python, and Power BI. The goal of this project was to uncover insights and visualize patterns to support data-driven decision-making.

Project Overview

#	SQL:

o	Performed data cleaning and transformation.

o	Executed queries to analyze accident trends, severity distribution, and contributing factors.

#Python:

o	Conducted time-series analysis and generated visualizations with libraries like Matplotlib and Pandas.

o	Performed advanced data manipulation for deeper insights.

# Power BI:

o	Developed an interactive dashboard to visualize key metrics such as accident severity, time trends, and risk factors.

o	Included filters and drill-through options for a dynamic user experience.

  Key Features

 

•	Data preprocessing and analysis using SQL and Python.

•	Interactive and visually compelling dashboard in Power BI.

•	End-to-end analytics workflow demonstrating multi-tool integration.

Repository Contents

•	SQL Scripts: Queries used for data extraction and analysis.

•	Python Scripts: Code for time-series analysis and visualization.

•	Power BI File: Interactive dashboard showcasing the analysis.

•	Dataset: Sample anonymized dataset (if permissible).

# Skills Demonstrated:

•	SQL querying and data modeling.

•	Python-based data manipulation and visualization.

•	Power BI dashboard design for interactive storytelling.

Feel free to explore the project, and don't hesitate to reach out with questions or feedback!