This project transforms raw sales data from Excel into actionable insights using Power BI. It includes interactive dashboards showing overall sales, top products, category performance, customer behavior, and regional trends. Explore KPIs, charts, and maps to support clear and data-driven decision-making.
This project is based on open-source data for educational purposes. It represents a complete sales analysis for company X. The analysis was initially started using Excel, but due to severe performance issues—such as frequent crashes, extreme slowness, and the inability to build and save interactive dashboards—the approach was shifted to Power BI.
While only static screenshots could be taken from Excel, the full project was successfully rebuilt in Power BI, enabling interactive dashboards, smooth analysis, and a better user experience.
- Challenge 1: Excel dashboard became very heavy and crashed frequently.
Solution: Rebuilt the entire project in Power BI, which handled large datasets efficiently.
- Challenge 2: Excel did not support fully interactive dashboards.
Solution: Used Power BI to create interactive visuals, slicers, and dynamic KPIs.
- Challenge 3: Saving and sharing dashboards from Excel was not possible.
Solution: Published the Power BI report online with interactive access through a shareable link.
- Challenge 4: The provided Excel file works smoothly for raw data exploration, but completing the full dashboard in Excel was not possible due to performance limitations.
Solution: The Excel file is included for reference and comparison with the final Power BI solution.
Tools Used:
Microsoft Excel & Microsoft Power BI
Dataset:
Sales data including: Products, Customers, Orders, Dates, Brands, Payment Methods, and Branches
Techniques Applied:
Data cleaning & formatting, Pivot tables & charts, Data modeling, DAX, and Dashboard design
1- Analyze total sales performance and identify overall business trends.
2- Highlight top-performing products and categories to understand demand patterns.
3- Compare sales across branches and regions to evaluate geographical performance.
4- Assess brand contributions to total revenue through percentage and tree map visuals.
5- Understand payment method distribution and customer preferences.
6- Provide key performance indicators (KPIs) for decision-making (total sales, number of customers, number of orders, active countries).
7- Deliver interactive dashboards that allow dynamic filtering by branch, brand, category, and time period.
The dataset contains 229 unique country entries, which is higher than the actual number of countries worldwide (~195). This discrepancy is due to the inclusion of:
Overseas territories (e.g., Guadeloupe, Bermuda, Greenland).
Regions with special administrative status (e.g., Hong Kong, Macao).
Disputed/limited-recognition areas (e.g., Western Sahara).
This reflects the dataset’s structure rather than a data error, and it provides additional geographical granularity for business analysis.
| Total Sales | 974,693.20 |
|---|
| Active Customers | 638 |
|---|
| Brand Name | Total Sales |
|---|---|
| Brand A | 164,291.50 |
| Brand B | 212,339.30 |
| Brand C | 196,291.50 |
| Brand D | 219,828.30 |
| Brand E | 181,942.60 |
| Grand Total | 974,693.20 |
| Category | Total Sales |
|---|---|
| Beauty | 187,779.30 |
| Electronics | 200,355.10 |
| Fashion | 221,302.00 |
| Home | 184,997.60 |
| Sports | 180,259.00 |
| Grand Total | 974,693.20 |
| Months | Total Sales |
|---|---|
| January | 97,353.20 |
| February | 83,658.10 |
| March | 76,986.90 |
| April | 78,257.00 |
| May | 75,055.50 |
| June | 78,716.00 |
| July | 81,131.70 |
| August | 94,159.30 |
| September | 76,538.80 |
| October | 83,520.70 |
| November | 74,302.60 |
| December | 75,013.30 |
| Grand Total | 974,693.20 |
| Payment Method | Total Sales |
|---|---|
| PayPal | 268,474.40 |
| Credit Card | 248,972.80 |
| Bank Transfer | 224,207.90 |
| Cash | 233,038.00 |
| Grand Total | 974,693.20 |
| Branches Name | Total Sales |
|---|---|
| Branch 5 | 182,583.20 |
| Branch 2 | 186,559.70 |
| Branch 1 | 199,602.80 |
| Branch 4 | 200,794.30 |
| Branch 3 | 205,153.20 |
| Grand Total | 974,693.20 |
| Category | Brand A | Brand B | Brand C | Brand D | Brand E | Grand Total |
|---|---|---|---|---|---|---|
| Beauty | 16,945.9 | 47,719.6 | 37,907.7 | 48,230.2 | 36,975.9 | 187,779.3 |
| Electronics | 40,237.7 | 32,167.3 | 45,580.3 | 50,415.8 | 31,954.1 | 200,355.1 |
| Fashion | 37,171.5 | 66,804.3 | 42,232.3 | 36,409.9 | 38,684.1 | 221,302.0 |
| Home | 33,578.8 | 38,963.1 | 34,144.0 | 36,480.6 | 41,831.1 | 184,997.6 |
| Sports | 36,357.6 | 26,684.9 | 36,427.3 | 48,291.9 | 32,497.4 | 180,259.0 |
| Grand Total | 164,291.5 | 212,339.3 | 196,291.5 | 219,828.3 | 181,942.6 | 974,693.2 |
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Top Products & Categories
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Branch Performance
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Brand Contribution
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Customer Overview
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Payment Methods
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Geographical Trends
Top-selling products & categories focus
Improve underperforming branches
Monitor customer behavior for personalized offers
Leverage popular payment methods
Geographical analysis for new markets
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Original Folder → The main Excel file containing data before cleaning contains ( Branches.xlsx, Brands.xlsx, Customers.xlsx, PaymentMethods.xlsx, Products.xlsx, Products.xlsx, Sales 2023.xlsx, Sales 2024.xlsx )
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Results and Dashboard:
The Excel file containing data & dashboard (Sales-Data-Analysis Project 2 Excel .xlsx)
The Power BI file (Sales Project 2 .pbix)
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Recommendations for Sales, Profitability & Performance.pdf → For Recommendations Details
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README.md → This file
You can explore the fully interactive sales dashboard online without needing Power BI Desktop. Click the link below to view the report:
Note: The dashboard works best on desktop browsers. Mobile browsers may have limited functionality.