This project analyzes financial performance using the Global Superstore dataset. It measures revenue, profit, and discount effects across products, regions, and customer segments. The goal is to uncover trends, identify profit drivers, and visualize key business insights through Power BI.

The dataset contains global retail transactions across multiple categories and regions. Key Fields:

Order Date: Time of sale

Region: Geographical market

Category & Sub-Category: Product classification

Sales, Profit, Discount, Quantity: Core financial metrics

Customer Segment & Ship Mode: Demographic and logistic details

Size: ~51,000 rows | Period: 2011–2014

Track sales and profit performance across dimensions.

Measure the effect of discounts on profitability.

Identify high-performing regions, products, and customer segments.

Visualize trends to guide business decisions.

How have sales and profits evolved over time?

Which regions and categories drive most revenue and profit?

Do discounts improve sales or reduce margins?

Which customers contribute most to revenue?

What is the overall profit margin by region and product type?

KPI Cards: Total Sales, Profit, Margin, Discount

Line Chart: Monthly Sales & Profit Trend

Bar Chart: Profit by Region / Category

Pie Chart: Revenue Share by Segment

Scatter Plot: Discount vs Profit

Map: Regional Sales Distribution

Table: Top 10 Customers by Total Spend

Power BI: Data modeling and visualization

Power Query: Data cleaning and transformation

DAX: Calculated measures and KPIs

Excel / CSV: Data preparation and validation

The dashboard delivers a concise, visual summary of the Global Superstore’s performance. It highlights how revenue, profit, and discount policies interact across global markets. This analysis supports decision-making in pricing, regional focus, and sales strategy.