Retail Analytics

Walmart Sales Analysis

End-to-end retail sales analytics project built using Python, SQL, Power BI and Tableau to uncover business insights, forecast future sales and support strategic decision-making.

Python SQL

Power BI

Tableau

Source Code View Dashboard

Executive Dashboard

Business Problem

Retail businesses generate massive sales data every day. Without proper analytics, identifying customer trends, regional performance and future demand becomes difficult. This project helps decision-makers monitor KPIs, forecast sales and improve profitability.

Dataset

Retail Transactions
Sales Records
Customer Data
Regional Sales
Product Categories
Historical Trends

Project Workflow

Data Collection

Imported retail sales dataset from Walmart transaction records and prepared it for analysis.

Data Cleaning

Removed duplicates, handled missing values, standardized columns and validated data quality using Python.

SQL Analysis

Wrote SQL queries to analyze sales, customer behaviour, product performance and regional trends.

Dashboard

Built interactive Power BI and Tableau dashboards for business stakeholders.

Key Performance Indicators

$2.45M

Total Sales

$323K

Total Profit

24.6K

Total Orders

18.9K

Customers

Business Insights

Sales Trend

Sales showed strong seasonal growth with peak performance during the holiday period.

Regional Performance

Western region generated the highest revenue, while South had the fastest growth rate.

Top Categories

Electronics contributed the highest share of overall revenue and profitability.

Recommendation

Improve inventory planning and increase promotions for high-performing categories.

Want to Explore the Complete Project?

View the complete source code, dashboard, SQL queries and documentation on GitHub.

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