Superstore Sales and Profit Analysis

This project provides a comprehensive analysis of the sales, profit, and customer segments for a superstore, leveraging a SQL-based data warehouse. It includes creating tables, transferring data from a source database, and conducting analyses on various aspects of sales and profitability. Key objectives of the project include:

Customer Segment Contribution: Identifying which customer segment generates the highest sales.

Profitability Analysis: Determining which product sub-category has the highest average profit margin.

Territory-Based Sales Trends: Analyzing how sales volumes vary across different territories.

Order Status Insights: Exploring differences in sales volume between different order statuses.

Influence Analysis: Comparing the impact of customer segment, territory, and product category on total sales.

Seasonal Sales Trends: Identifying seasonal trends in sales volume, including variations across product categories.

Discount Impact on Profitability: Examining the relationship between discount levels and profit margins.

Delivery Time Analysis: Assessing the effect of order status on delivery time.

Growth Analysis: Performing a year-over-year analysis of sales growth across product sub-categories.

Predictive Sales Model: Preparing data for a predictive model to forecast next-quarter sales, factoring in product category, customer segment, and territory.

This SQL project creates and populates tables for customers, products, orders, and order details, then applies SQL queries to extract valuable insights. The structured approach provides a foundation for understanding key performance metrics, influencing factors, and growth opportunities within the superstore's data.