Project Workflow: 1️⃣ Data Cleaning with Python – Processed raw sales data to remove inconsistencies, handle missing values, and prepare it for analysis. 2️⃣ Data Loading into SQL Server – Connected Python to SQL Server Management Studio and loaded the cleaned dataset for structured querying. 3️⃣ Data Analysis with SQL – Performed detailed analysis including:
Identifying the most popular payment methods overall and per branch.
Calculating total quantity sold per payment method.
Finding the highest-rated categories per branch.
Determining the busiest days of the week and month for each branch.
Categorizing sales into Morning, Afternoon, and Evening shifts.
Calculating total profit per category and identifying the top 5 branches with the highest revenue decrease year-over-year.