An end-to-end project demonstrating data cleaning, analysis, and interactive dashboard creation in Microsoft Excel to uncover sales insights.

• About The Project
• Dashboard Features
• Tech Stack
• Methodology
• Key Insights
• How To Use
• Connect with Me

This project transforms a raw, messy dataset of bike sales into a powerful business intelligence tool. The core objective was to perform a full data analysis cycle:

• Clean and Preprocess raw data to ensure accuracy.
• Analyze the cleaned data using Pivot Tables to identify trends.
• Visualize findings through an interactive and user-friendly dashboard.

• ✅ KPI Cards: Main metrics like Total Sales, Profit, and Quantity Sold are prominently displayed.
• ✅ Regional Performance: Bar charts to compare sales and profit across different regions.
• ✅ Product-wise Analysis: Breakdown of sales by product category.
• ✅ Monthly Sales Trends: A line chart to track performance over time and identify seasonality.
• ✅ Dynamic Slicers: Interactive filters for Region, Gender, and Age Group that update the entire dashboard in real-time.

• Microsoft Excel
  • Formulas
  • Conditional Formatting
  • Pivot Tables & Pivot Charts
  • Slicers & Timelines
  • Dashboard Design

1. Data Cleaning: Removed duplicates, handled blank cells, and corrected data type inconsistencies.
2. Data Transformation: Standardized text entries (e.g., 'F' to 'Female') and created new columns for analysis (e.g., Age Brackets).
3. Aggregation: Used Pivot Tables as the engine to summarize vast amounts of data into meaningful metrics.
4. Visualization: Built Pivot Charts from the aggregated data and assembled them into a cohesive dashboard layout.
5. Interactivity: Connected all charts and tables with Slicers to enable drill-down analysis.

• Finding: Customers with higher average incomes are more likely to purchase a bike.
• Insight: Males who purchase bikes represent the segment with the highest average income, indicating strong purchasing power.

• Finding: The overwhelming majority of purchases are from customers with a commute of 0-1 miles.
• Insight: This suggests bikes are primarily used for short-distance travel or recreation, not long commutes. This is a key insight for marketing messaging.

• Finding: The middle-aged group (31-54) dominates bike sales.
• Insight: Marketing and product development should be heavily focused on this age bracket, as adolescents and seniors show significantly lower purchase rates.

1. Download the Bike Sales Project.xlsx file from the link below.
2. Open the file in Microsoft Excel (2016 or later recommended).
3. Navigate to the 'Dashboard' sheet.
4. Interact with the Slicers on the right to filter the data and explore insights!

➡️ Download the full Excel File Here

Have feedback or want to connect? Feel free to reach out!

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