MySQL Protfolio Project

In today's data-driven business landscape, understanding sales trends and performance metrics is crucial for decision-making and strategy development. This project portfolio focuses on utilizing MySQL to analyze sales data, providing insightful and actionable findings. Through this project, I employed various SQL techniques—such as data extraction, transformation, aggregation, and complex querying—to examine key sales metrics like total revenue, product performance, customer segmentation, and regional sales trends.

The goal of this project is to demonstrate how MySQL can be leveraged to derive meaningful insights from raw sales data, improving business intelligence and supporting strategic initiatives in sales and marketing.

There are some steps must be followed :

Link for the dataset: https://github.com/Princekrampah/WalmartSalesAnalysis/blob/master/WalmartSalesData.csv.csv

CREATE NEW DATABASE

CREATE TABLE

Show the Table:

Then, we can see the import data

Add the time

Add the time_of_day

In here, we want to make the automatic time

Let's count the payment from different method

Count the number of Product_Line

Sum(Total) of the months

Now, we can make combination from branch, city, and sum(total)

Count the average(tax) from product_line

This project highlights the capabilities of MySQL for comprehensive sales data analysis. Using MySQL, I performed data cleaning to ensure the accuracy and consistency of the dataset, which is essential for reliable analysis. Once the data was prepared, I utilized SQL queries to analyze key business metrics such as sales performance, customer behavior, and product trends.

In addition to data cleaning and business analysis, MySQL allowed for advanced functions like filtering, aggregation, and segmentation, enabling the identification of growth opportunities, sales patterns, and performance bottlenecks. This project demonstrates how MySQL can be effectively used to transform raw sales data into actionable insights for business decision-making.