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Power BI · SQL · Business Intelligence

Revenue Intelligence &
Profitability Analysis

An interactive BI dashboard built with SQL, Excel, and Power BI to analyze sales performance, profitability, customer contribution, and budget allocation — turning raw business data into strategic decisions.

📊 Power BI 🗄️ SQL 📗 Microsoft Excel 🧮 DAX 📈 Business Intelligence
Revenue Intelligence & Profitability Analysis · Power BI
Overview

Project Overview &
Problem Statement

The Revenue Intelligence & Profitability Analysis Dashboard is an interactive Business Intelligence project developed using SQL, Excel, and Power BI. It analyzes sales performance, profitability, customer contribution, and budget allocation to support data-driven strategic decisions.

Organizations often struggle to monitor profitability, budget utilization, and customer contribution across different regions and products. This dashboard centralizes business data into a single interactive reporting solution — enabling faster and more informed decisions across sales channels, product lines, and geographies.

The objective was to transform raw business data into meaningful visual insights, track KPIs in real time, compare revenue against budget targets, and surface strategic recommendations for growth and optimization.

Project Details
Category BI Dashboard
Tools Power BI · SQL · Excel · DAX
Data Prep SQL Database · Excel Cleaning
Domain Revenue & Profitability
Filters Channel · Product · Region · Customer
Source Files GitHub →
Metrics

Project at a Glance

💰
206M
Total Sales
📈
143M
Total Profit
🎯
69%
Profit Margin
📊
62M
Total Budget
Analysis

Key Insights

01
Wholesale Leads Revenue Share
The wholesale channel contributes the highest share of total revenue, making it the most critical sales channel to maintain and optimize for continued growth.
02
Top Products Drive Majority of Sales
A concentrated group of top-performing products generates a disproportionately large portion of total sales — a classic Pareto pattern warranting focused inventory and marketing strategy.
03
Several Products Exceed Budget Targets
Revenue vs. budget comparison reveals that certain products have outperformed their allocated targets, indicating strong demand that may justify increased budget allocation.
04
Revenue Balanced Across Key Customers
Customer contribution analysis shows revenue is relatively distributed across major customers, reducing over-reliance risk and suggesting a healthy, diversified customer base.
05
European Regions Show Strong Concentration
Geographic sales data highlights strong performance concentration in European regions, pointing to an established market presence and potential for deeper regional penetration.
06
High Profit Margin at 69.6%
A profit margin of 69.6% against total sales signals strong operational efficiency and pricing strategy — well above typical industry benchmarks for product-based businesses.
Stack

Tools & Technologies

📊 Power BI
🗄️ SQL
📗 Microsoft Excel
🧮 DAX
🔗 Data Modeling
🔑 Primary & Foreign Keys
🧹 Data Cleaning
📌 KPI Cards
🗺️ Geographic Visualization
🎛️ Dynamic Filtering
Functionality

Key Features

🎛️
Interactive Power BI Dashboard
Fully dynamic Power BI report with cross-filtering across all visuals — drill down by sales channel, product, customer, or city at any point in the analysis.
📌
KPI Tracking Cards
Prominent KPI cards display Total Sales, Total Profit, Profit Margin, and Total Budget at a glance — built using DAX measures for accurate, real-time calculation.
💹
Revenue vs. Budget Comparison
Side-by-side visual comparison of actual revenue against allocated budgets across products and regions, highlighting over- and under-performing areas.
🗄️
SQL Database & Data Modeling
Relational database created in SQL with primary and foreign keys, structured table relationships, and direct Power BI connection for seamless reporting.
🗺️
Geographic Sales Visualization
Regional sales performance mapped geographically to surface city and country-level concentration, supporting territory planning and expansion strategy.
👥
Customer Contribution Analysis
Breakdown of revenue share by customer reveals top contributors and distribution balance, informing retention priorities and customer engagement strategies.
Data

Dataset Information

The project uses a structured relational dataset imported into SQL tables and preprocessed using Microsoft Excel, then connected to Power BI for modeling, DAX measure creation, and visualization.

Data fields included:

  • Sales transactions — amount, profit, quantity
  • Budget allocations by product and region
  • Customer identifiers and contribution data
  • Regional and city-level geographic fields
  • Product categories and sales channel classification
  • SQL relationships via Primary & Foreign Keys
📁 Project Files — via GitHub
📊
Revenue_Analysis_Dashboard.pbix
Power BI Report File
GitHub
🗄️
sales_analysis.sql
SQL Database Script
GitHub
📗
sales_table_PR.csv
Sales Dataset (CSV)
GitHub
📗
budget_data_PR.csv
Budget Data (CSV)
GitHub
📗
customer_data_PR.csv
Customer Data (CSV)
GitHub
📗
region_data_PR.csv
Region Data (CSV)
GitHub

All files hosted on GitHub — click any row to download.

Conclusion

Takeaway

This dashboard demonstrates end-to-end Business Intelligence capability — from SQL database design and data modeling to DAX-powered KPI calculations and interactive Power BI storytelling. With a 69.6% profit margin surfaced and revenue vs. budget gaps clearly visualized, it proves how combining SQL, Excel, and Power BI can transform scattered business data into a centralized decision-making engine — enabling leaders to act on real insights rather than assumptions.

Interested in
collaborating ?

Feel free to reach out for feedback, collaboration, or any data analytics opportunities.

rout06738@gmail.com GitHub Profile