Car Sales Trends Dashboard

Skills, Tech Stack, and Libraries

1. Skills: Data Visualization, Data Wrangling, Statistical Analysis, Dashboard Design

2. Tech Stack: Tableau, Power BI, SQL, Python

3. Libraries: Pandas, Matplotlib, Seaborn

Description and Approach

Objective:

I designed and developed an interactive dashboard to visualize car sales trends, providing insights into sales performance across regions, car models, and customer demographics. The goal was to enable strategic decision-making based on real-time and historical data.

Approach:

1. Data Collection and Cleaning: I imported sales data from multiple sources, including SQL databases and CSV files, using Python. The data was cleaned and standardized using Pandas to ensure consistency and accuracy.

2. Exploratory Data Analysis (EDA): Conducted in-depth EDA with Matplotlib and Seaborn to uncover sales patterns, identify popular car models, and analyze seasonal trends. This step helped identify key metrics for the dashboard, such as sales growth rates and revenue contributors.

3. Data Transformation: Aggregated and grouped the data (e.g., monthly sales, region-wise performance) using SQL queries. I calculated KPIs like average revenue per region, sales by customer demographics, and market share percentages to present actionable insights.

Dashboard Design:

1. Leveraged Tableau to design an intuitive and interactive dashboard. The dashboard included: Bar charts for sales by region.

2. Pie charts for market share by car model.

3. Line charts to visualize monthly and seasonal sales trends.

4. I implemented dynamic filters to allow stakeholders to explore data by time period, car type, and region.

Code Flow:

1. Loaded data into Pandas for cleaning and pre-processing.

2. Executed SQL queries to aggregate and transform data.

3. Exported the cleaned and processed data to Tableau for visualization.

4. Designed and deployed the dashboard for stakeholder use.

Results

The project delivered a user-friendly dashboard that provided comprehensive insights into car sales trends:

• Top-Performing Models: Identified the best-selling models, enabling targeted marketing strategies.

• Seasonal Trends: Highlighted peak sales periods and underperforming months, aiding inventory management.

• Regional Analysis: Uncovered regional performance patterns, informing resource allocation and dealership strategies.

The dashboard empowered sales and marketing teams with data-driven insights, enhancing their ability to make informed strategic decisions.

Git Link

For more information and code, visit the Git link.