BIKE BUYERS DATA ANALYSIS IN EXCEL
PROJECT OVERVIEW -
This project focuses on data cleaning, transformation, and dashboard creation using a bike buyers dataset. It leverages Pivot Tables, slicers, and charts to analyze customer trends, purchasing patterns, and key insights based on factors like income, age, and occupation.
FEATURES -
Data Cleaning & Preprocessing – Handling missing values, formatting, and structuring data.
Pivot Tables & Charts – Summarizing and visualizing key metrics.
Interactive Dashboard – Using slicers for dynamic filtering.
Customer Insights – Understanding trends based on demographics.
TECHNOLOGIES USED -
Microsoft Excel – Data analysis, Pivot Tables, and dashboards
DATASETS -
The dataset includes customer demographics, income, commute distance, occupation, and purchase behavior.
HOW TO USE -
- Open the Excel file.
- Explore the bike_buyers sheet for raw data.
- Check the Dashboard sheet for insights and visualizations.
- Use slicers to filter and analyze trends interactively.
PROJECT INSIGHTS -
- Higher-income groups tend to purchase bikes more frequently.
- Commute distance influences purchasing decisions.
- Certain occupations show higher bike purchase rates.
FUTURE IMPROVEMENTS -
-Automate data updates with Power Query
-Integrate advanced Excel functions for deeper insights
-Export dashboards for better reporting