Walmart Sales Data Analysis

Walmart Sales Data Analysis Project

Goal: The goal of this project was to explore and analyze Walmart sales data using SQL to gain insights into the top-performing branches and products, sales trends, and customer behavior. The aim was to improve and optimize sales strategies based on the findings.

Insights:

• Top-Performing Branches: Identified the branches with the highest sales and revenue.
• Product Performance: Analyzed different product lines to understand which products performed best and which needed improvement.
• Sales Trends: Evaluated sales trends over time to measure the effectiveness of sales strategies and identify areas for improvement.
• Customer Segmentation: Studied customer behavior to uncover different customer segments, purchase trends, and profitability.
• Revenue and Profit Analysis: Calculated key metrics such as cost of goods sold (COGS), value-added tax (VAT), gross income, and gross margin percentage.

Discovering and Presenting Insights:

• Data Collection and Organization: Gathered historical sales data from the Kaggle Walmart Sales Forecasting Competition, including details on sales transactions, branches, customer types, product lines, and more.
• Data Wrangling: Inspected data for null and missing values, and applied data cleaning techniques using SQL to ensure data quality.
• Feature Engineering: Created new columns such as time of day, day name, and month name using SQL queries to provide additional insights.
• Exploratory Data Analysis (EDA): Conducted EDA using SQL to answer business questions related to product performance, sales trends, and customer behavior.
• Revenue and Profit Calculations: Calculated key financial metrics using SQL queries to evaluate the profitability of different branches and product lines.

This project provides valuable insights into Walmart's sales data, helping to identify top-performing branches and products, understand sales trends, and improve customer segmentation. The analysis supports effective decision-making and optimization of sales strategies through detailed data exploration using SQL.