This project delivers an end-to-end revenue performance analysis for an e-commerce dataset using PostgreSQL and Power BI.
The objective was to transform raw transactional data into structured business intelligence by designing a relational data model, performing data validation, and building an interactive executive dashboard for revenue and profitability insights.
To analyze transactional sales data and generate actionable insights related to:
- Revenue growth trends
- Profitability analysis
- Product performance
- Regional contribution
- Customer payment behavior
- Revenue concentration (Pareto analysis)
- PostgreSQL – Data modeling, cleaning, KPI computation
- Excel – Initial dataset formatting & validation
- Power BI – Interactive dashboard & visualization
The project follows a Star Schema model:
- Sales (Fact Table) – Transaction-level details (Order ID, Revenue, Profit, Region, Payment Mode)
- Products (Dimension Table) – Product metadata (Category, Cost Price)
A consolidated analytical view was created to simplify reporting and KPI calculations.
Performed structured validation to ensure data integrity:
- Missing value detection using FILTER clause
- Duplicate order validation
- Referential integrity checks between Sales and Products
- Handling unmatched product IDs using controlled “UNKNOWN” categorization
- Total Revenue
- Total Profit
- Profit Margin %
- Average Order Value (AOV)
- Monthly Revenue Trend (MoM)
- Category-wise Revenue & Profit
- Regional Sales Distribution
- Payment Mode Performance
- Product Revenue Contribution % (Calculated using SQL Window Functions)
- Identified revenue concentration among top-performing products (Pareto effect).
- Evaluated category-level profitability to support pricing strategy.
- Analyzed seasonal revenue patterns using time-based aggregation.
- Assessed regional contribution to optimize market focus.
- Examined customer payment preferences for operational insights.
- Executive KPI Cards (Revenue, Profit, Margin, AOV)
- Monthly Revenue & Profit Trend Analysis
- Category & Region Breakdown
- Product Contribution Visualization
- Interactive Slicers (Date, Category, Region, Payment Mode)
The dashboard enables dynamic filtering for executive-level reporting.
- Import CSV files into PostgreSQL.
- Execute the SQL script to create tables and analytical view.
- Open the Power BI (.pbix) file.
- Refresh data connection.
Rachit Jain
Aspiring Data Analyst | Business Analytics Enthusiast
Connect With Me
LinkedIn: (https://www.linkedin.com/in/itsrachitjain/) GitHub: (https://github.com/itsrachitjain)