Credit Card Financial Dashboard

Type: Data Analytics Project | Tool: Power BI + SQL

An interactive Power BI dashboard built using transaction and customer data from a SQL database to analyze credit card business performance, customer demographics, and spending patterns.

Designed as a portfolio project to demonstrate data analysis, SQL-based data extraction, and business insight generation skills.

Objective

To analyze and monitor credit card business performance by evaluating revenue, interest earned, and transaction patterns across customer segments and spending categories.

Dashboard Preview

Transaction Report

Customer Report

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Dataset

• credit_card.csv — Transaction-level credit card data containing:

  • Card category, transaction amount, interest earned
  • Payment mode (Swipe, Chip, Online)
  • Expenditure type, week number, quarterly data

• customer.csv — Customer demographic details containing:

  • Age group, income level, education, job type
  • State, dependent count, satisfaction score

• SQL database — Data extraction and transformation layer

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Tools & Technologies

• Power BI — Dashboard design, data modeling, and visualizations
• Power Query — Data cleaning & transformation
• DAX — KPI calculations (Revenue, Interest Earned, WoW variance, Activation Rate)
• SQL — Data extraction & transformation from relational database
• CSV — Raw data source

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Key Features

Transaction Report

• Total Revenue (57M), Transaction Amount (45.5M), Interest Earned (8M), Transaction Count (667.2K)
• Revenue breakdown by card category, expenditure type, and payment mode
• Week-over-week (WoW) revenue variance tracking
• Quarterly revenue and transaction count comparison (Q1–Q4)

Customer Report

• Revenue segmented by age group, income level, education, and job type
• State-wise and dependent-count revenue distribution
• Customer Satisfaction Score (CSS): 3.19
• 30-day activation rate: 57.46%
• Delinquency rate analysis by customer job segment

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Key Insights

• Total revenue stands at $57M with $8M in interest earned across 667K+ transactions
• Blue card holders generate the highest revenue at $47M out of total $57M
• Swipe transactions dominate at $36M, compared to Chip ($17M) and Online ($4M)
• Graduate customers contribute the highest revenue at $23M by education type
• Businessmen lead revenue by job category at $18M
• Q4 recorded the highest transaction count at 173.2K
• 57.46% of customers activated their card within 30 days

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Business Impact

This dashboard enables financial teams to:

• Monitor real-time credit card revenue and transaction performance
• Identify high-value customer segments for targeted marketing
• Track delinquency risk and activation rates for operational decisions
• Analyze spending behavior across categories to optimize card offerings

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How to Use

1. Download the .pbix file from this repository
2. Open in Power BI Desktop (free download at powerbi.microsoft.com)
3. The dashboard loads with all data pre-connected — no additional setup required
4. Use quarter filters (Q1–Q4) and gender/card-type slicers to explore the data
5. Hover over any chart for detailed tooltips
6. To connect your own SQL database, go to Home → Transform Data and update the data source connection

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Project Structure

Credit_Card_Financial_Dashboard/
├── Credit_Card_Financial_Dashboard.pbix    # Power BI dashboard file
├── Credit_Card_Transaction_Dashboard.sql   # SQL queries for data extraction
├── credit_card.csv                         # Transaction dataset
├── customer.csv                            # Customer dataset
├── Credit_Card_Report_transaction.pdf      # Transaction report (static export)
└── Credit_Card_Report_customer.pdf         # Customer report (static export)

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Author

Fizza Shabbir — LinkedIn | GitHub