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This Power BI dashboard provides a comprehensive Car Sales Analysis for the USA. Here’s a tutorial-style explanation of how it’s structured and how it works:

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πŸ”· 1. Dashboard Layout

The dashboard is designed with a combination of KPI cards, bar charts, pie charts, and treemaps, along with filter slicers on the right for interactivity.


πŸ”· 2. Top-Level KPIs (Key Performance Indicators)

  • These cards show high-level metrics such as:
    • Average of Annual Income
    • Average Price of Cars
    • Total Sales in USD
    • Total Cars Sold
    • Total Companies Count

These help quickly assess the overall business performance.


πŸ”· 3. Visualizations

  • Sales by Body Style: A donut chart showing which car styles (SUV, Sedan, etc.) are most popular.
  • Sales by Color: A combo chart (bar + line) indicating both sales value and the count of cars sold by color.
  • Sales by Company: A bar and line chart showing which companies are leading in terms of revenue and units sold.
  • Sales by Dealer Region: A horizontal bar chart breaking down sales by geographic regions.
  • Sales by Engine Type: A pie chart comparing types of engines (e.g., Overhead Cam vs Double Overhead Cam).
  • Sales by Gender: A pie chart showing the gender distribution of car buyers.
  • Sales by Transmission: Another pie chart comparing automatic vs manual transmissions.
  • Sales by Model (Treemap): A treemap visualizing the revenue contribution by individual car models.

πŸ”· 4. Interactive Filters (Slicers)

  • On the right, slicers allow you to filter the entire report based on:
    • Transmission
    • Body Style
    • Color
    • Company
    • Dealer Region
    • Engine Type
    • Gender
    • Model

Users can select from these filters to drill down and focus on specific data segments.


πŸ”· 5. Interactivity

Clicking on any chart element (e.g., a car brand or region) automatically updates the other visuals to reflect filtered data β€” a key feature of Power BI that enhances data exploration.


πŸ”· 6. Purpose

This dashboard is ideal for:

  • Business decision-makers to analyze trends and performance.
  • Marketing teams to identify customer preferences.
  • Regional managers to compare dealer performance.