This project conducts Exploratory Data Analysis (EDA) for Global Electronics, a leading consumer electronics retailer, to uncover actionable insights that enhance customer satisfaction, optimize operations, and drive business growth. The analysis spans customer demographics, sales trends, product performance, and store operations.
- Data Cleaning & Preprocessing
- Exploratory Data Analysis (EDA)
- Python Programming
- SQL Data Management
- Power BI Visualization
A set of interactive dashboards and visual analyses for a global electronics dataset.
This repository contains exported dashboard images that showcase the following analyses:
- Product Analysis
- Store Analysis
- Sales Analysis
- Customer Analysis
- Main Dashboard / Executive Summary
Filename: Main_Dashboard_DI.png
This page gives a high-level business overview for leadership team:
Insights shown:
Total revenue, profit, orders, and growth trends
Top-performing regions and product categories
Quick comparison of store contributions
Business Value: Helps executives track KPIs and make fast strategic decisions.
Filename: Product_Analysis_DI.png
This focuses on identifying winning and underperforming products:
Insights shown:
Best-selling product categories
Profit contribution by product line
High-demand vs low-selling items
Business Value: Guides decisions on product optimization, marketing focus, and inventory planning.
Filename: Store_Analysis_DI.png
This page highlights store performance across locations:
Insights shown:
Revenue by region and by store type
Footfall vs. sales correlation
Top and bottom store ranking
Business Value: Supports store expansion planning and resource allocation to improve underperforming locations.
Filename: Sales_Analysis_DI.png
Analytical breakdown of overall sales performance:
Insights shown:
Monthly and seasonal trends
Order volume and revenue growth patterns
Contribution of discounts and pricing
Business Value: Helps forecast demand and shape pricing and promotional strategies.
Filename: Customer_Analysis_DI.png
Customer behavior and segmentation insights:
Insights shown:
Customer lifetime value segments
New vs returning customers
Purchase patterns by demographics
Business Value: Strengthens CRM initiatives and targeted marketing campaigns.
- High-quality dashboard exports (PNG files listed above) created from a Power BI / dashboarding workflow.
- Each image highlights data-driven insights such as revenue trends, product performance, regional sales, customer segmentation, and top storefront metrics.
Retail Analytics in the Electronics Industry
Global Electronics seeks to leverage its customer, product, sales, and store data to:
- Improve marketing strategies and customer segmentation.
- Optimize inventory management and sales forecasting.
- Enhance store performance and international pricing strategies.
- Customer Insights: Tailor marketing campaigns based on demographics and purchase behavior.
- Product Optimization: Identify top-performing products and categories.
- Store Expansion: Evaluate high-performing regions for new stores.
- Currency Impact: Adjust international pricing using exchange rate analysis.
- Handle missing values, convert data types, and merge datasets.
- Tools: Python (Pandas, NumPy).
- Create tables and load preprocessed data using SQL.
- Tools: PostgreSQL/MySQL.
- Analyze customer demographics, sales trends, and product performance.
- Tools: Python (Matplotlib, Seaborn).
- Connect to SQL database and build interactive dashboards.
- Tools: Power BI, Tableau.
- Extract insights like top-selling products, customer segmentation, and sales by region.
- Primary Data: Customer profiles, product details, sales transactions, store info, and currency exchange rates.
- Dataset Names: [Download Here]Customers.csv ,Data_Dictionary.csv ,Exchange_Rates.csv,Products.csv,Sales.csv,Stores.csv
- Demographic distribution (age, gender, location).
- Purchase patterns (order value, frequency).
- Customer segmentation.
- Trends, seasonality, and top-performing products/stores.
- Currency exchange impact.
- Popularity, profitability, and category performance.
- Performance metrics (sales/sq. meter, geographical trends).
- Cleaned and Integrated Datasets
- EDA Report with actionable insights.
- Interactive Dashboards (Power BI/Tableau).
- SQL Queries for key business questions.
- Recommendations for marketing, inventory, and expansion.