BI Dashboard Case

A Power BI portfolio project for payment and product analytics.

Overview

This project demonstrates the design and development of an interactive Power BI dashboard using synthetic payment transaction data.

The dashboard focuses on key product and financial metrics, including:

• Payment Volume
• Transaction Count
• Success Rate
• Commission Revenue
• Active Users
• Payment Volume by Category
• Daily Payment Volume
• Transaction Count by Category
• Top Users by Payment Volume
• Transaction Status

Dashboard Preview

Dataset

The project uses a synthetic dataset:

dashboard_data.xlsx

Main fields:

• date
• user_id
• category
• amount
• commission
• status

All data in this repository is synthetic and created specifically for demonstration purposes.

KPI Definitions

The main KPIs used in the dashboard are documented in:

kpi_definitions.md

Key measures include:

• Payment Volume
• Transaction Count
• Successful Transactions
• Success Rate
• Commission Revenue
• Active Users
• Average Transaction Amount

Power BI Measures

The dashboard uses DAX measures to calculate:

• successful payment volume;
• transaction count;
• successful transaction count;
• success rate;
• commission revenue;
• active users;
• average transaction amount.

Interactive Filters

The dashboard includes interactive filters for:

• Date
• Status
• Category

These filters dynamically update the KPI cards and visualizations.

Dashboard Visuals

The report includes:

• KPI cards
• Column charts
• Line chart
• Donut chart
• User-level table
• Interactive slicers

Tech Stack

• Power BI
• DAX
• Microsoft Excel
• Data Visualization
• Product Analytics
• Payment Analytics

Project Structure

• payment_dashboard.pbix — Power BI dashboard
• dashboard_screenshot.png — dashboard preview
• dashboard_data.xlsx — synthetic dataset
• kpi_definitions.md — KPI documentation
• README.md — project documentation

Skills Demonstrated

• Power BI dashboard development
• DAX measures
• KPI design
• Data visualization
• Product analytics
• Payment analytics
• Financial analytics
• Interactive reporting
• Dashboard design

Data Privacy

All data used in this repository is synthetic and created specifically for portfolio demonstration purposes.

The project does not contain confidential, customer, production, or employer data.

Future Improvements

• Add monthly and weekly trend analysis
• Add MAU / DAU metrics
• Add retention analysis
• Add category contribution analysis
• Add anomaly detection
• Add drill-through pages
• Add tooltip pages
• Add executive summary page