Car Sales Analysis Using Python, SQL, and Power BI

This repository contains a comprehensive analysis of car sales data using Python, SQL, and Power BI. The project aims to provide actionable insights into sales trends, dealer performance, and key metrics such as total revenue and average price. The analysis involves processing and visualizing data to uncover sales patterns and support strategic decision-making.

Dataset

The dataset includes the following fields:

• car_id: Unique identifier for each car
• Date: Date of sale
• Customer Name: Name of the customer
• Gender: Gender of the customer
• Annual Income: Annual income of the customer
• Dealer_Name: Name of the dealer
• Company: Car manufacturer or company
• Model: Car model
• Engine: Type of engine
• Transmission: Type of transmission (Automatic/Manual)
• Color: Color of the car
• Price ($): Price of the car
• Dealer_No: Dealer number
• Body Style: Body style of the car (e.g., Sedan, SUV)
• Phone: Contact number of the dealer
• Dealer_Region: Region where the dealer is located

Project Overview

1. Data Analysis and Cleaning:

   • Used Python for data manipulation, statistical analysis, and visualization.
   • Performed data cleaning tasks such as handling missing values, duplicates, and data type conversions.

2. SQL Queries:

   • Executed SQL queries to extract and analyze data directly from the database.
   • Focused on sales performance, customer demographics, and regional analysis.

3. Power BI Visualizations:

   • Created interactive dashboards and reports to visualize sales trends, dealer performance, and customer insights.
   • Utilized Power BI to present findings and support data-driven decision-making.

Thank You

Feel free to explore the project and reach out if you have any questions or feedback.

DASHBOARD