This project showcases a complete Sales Data Analysis & Visualization using Power BI, based on the Global Superstore 2016 dataset. The goal is to extract meaningful business insights, visualize key metrics, and help stakeholders make data-driven decisions.
- Source: Global Superstore 2016 (Sample Dataset)
- Data Scope: Global orders, customers, products, sales, and shipping details
- Key Fields:
- Order Date, Ship Date, Region, Country, Category, Sub-Category
- Sales, Profit, Quantity, Discount, Shipping Cost
- Clean and transform raw sales data in Power BI
- Build interactive dashboards for Sales, Profit, Region-wise Performance
- Identify key trends, top-selling products, and underperforming regions
- Provide actionable business insights with data storytelling
| Tool | Purpose |
|---|---|
| Power BI | Data Cleaning, Modeling, DAX, Dashboard Building |
| Data Analysis | Sales Trend Analysis, Profitability Analysis |
| Data Visualization | KPIs, Charts, Maps, Filters, Slicers |
- 🚀 Sales & Profit Overview
- 🌍 Region & Country-wise Performance
- 📦 Product Category & Sub-Category Analysis
- 💰 Top & Bottom Performing Segments
- 📈 Interactive Visualizations with Slicers & Filters
- Download the Global Superstore Dataset
- Open the provided Power BI report (.pbix file)
- Explore the dashboards and interact with visualizations
This project is part of my data analytics learning journey. It reflects my skills in data analysis, Power BI dashboarding, and business reporting.
My focus was to turn raw data into clear insights for business decision-making.
If you want to collaborate or have feedback, feel free to connect with me on LinkedIn or drop a message!