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Data-Visualization-and-Storytelling

Used Car Sales Analysis Dashboard 🚗📊

This repository contains my submission for Task 2: Data Visualization and Storytelling using Power BI for the Data Analyst internship program.


📁 Dataset Used

  • Used car sales data (CSV format)
  • Contains columns like: year, make, model, state, sellingprice, mmr, odometer, color, etc.

🛠 Tools Used

  • Power BI Desktop
  • GitHub

📊 Visualizations

  1. Sum of Selling Price by Make
  2. Average Selling Price by Year (Line & Column Chart)
  3. Sales by State (Bar Chart)
  4. Selling Price by Car Color (Donut Chart)
  5. Odometer vs Selling Price (Scatter Plot)
  6. MMR Insights (Card visuals)

📌 Key Insights

  • Ford, Chevrolet, and Nissan dominate in total revenue.
  • Average car price increases significantly after 2010.
  • Black and white are the most preferred car colors.
  • Lower odometer = higher selling price.
  • Average MMR is approx. 13.77K — useful for profit benchmarking.

Data Story

📖 Data Story: Used Car Sales Analysis Introduction:

This dashboard presents an analytical view of a used car sales dataset. It highlights key trends related to car make, production year, geographic region, odometer readings, color preferences, and market benchmarks (MMR). The goal is to turn raw sales data into meaningful business insights.

  1. Market Leaders – Car Makes

A bar chart of total selling price by make reveals that Ford, Chevrolet, and Nissan are top performers. These brands dominate the resale market both in volume and value, reflecting their wide acceptance and availability.

Insight: Focus inventory and promotions on top-selling makes for maximum revenue impact.

  1. Regional Performance – Sales by State

State-wise sales analysis shows that Georgia, Texas, and California generate the highest revenue from used car sales. These states are critical markets with high transaction volumes.

Insight: Dealers and platforms should prioritize marketing and supply chains in these high-performing regions.

  1. Time Influence – Year vs Selling Price

Average selling price trends by production year reveal that vehicles manufactured after 2010 have significantly higher resale value. Older models from the 1990s and early 2000s sell for much less.

Insight: Focus on newer model years (post-2010) to attract higher-paying buyers and increase profitability.

  1. Buyer Preferences – Color Popularity

Donut chart data shows that black (22.6%), white (20.5%), and gray are the most popular exterior colors. Neutral tones dominate consumer choice in the used car segment.

Insight: Stocking black, white, and gray vehicles improves turnover rates due to higher demand.

  1. Wear & Tear – Odometer vs Price

A scatter plot of odometer readings against selling price reveals an inverse relationship. As mileage increases, the selling price drops significantly, especially beyond 100,000 miles.

Insight: Low-mileage vehicles retain higher value and should be prioritized in procurement and promotion.

  1. Market Benchmarking – MMR Analysis

The average Manheim Market Report (MMR) value across vehicles is around 13.77K. Comparing this benchmark with actual selling prices helps estimate margins and evaluate competitiveness.

Insight: Dealers can use MMR data to optimize pricing strategy and improve profit margins.

Conclusion:

This data visualization project transforms raw vehicle sales data into actionable insights. It empowers stakeholders to:

Make informed decisions on inventory and pricing

Identify high-value markets and vehicle types

Optimize sales strategy based on buyer behavior and market trends

By combining Power BI’s visual power with business storytelling, the dashboard presents a clear, concise, and compelling view of the used car resale landscape.

🎯 Outcome

This dashboard tells a clear story about car resale trends, regional performance, customer preferences, and factors affecting pricing.


📷 Screenshots

Dashboard Screenshot

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DATA ANALYST INTERNSHIP from Event labs-Task 2

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