To develop comprehensive credit card weekly dashboard that provides real-time insights into key performance metrics and trends, enabling stakeholders to monitor and analyze credit card operations effectively.
Financial dataset
- Import Data From SQL Database.
- Prepare CSV File
- Create table in SQL
- Import CSV into SQL
- Data Processing and DAX Queries
- Grouped customers by age and income to derive insights.
- Calculated Revenue with annual fees, total transaction amount and interest earned.
- Derived week numbers using DAX Query.
- Calculated week by week change in revenue ( (current_week_revenue - previous_week_revenue) / previous_week_revenue ).
- Create Dashboard and derive insight
- calculated sum of revenue, total transaction amount and interest earned by card category.
- visualised revenue by customer's job, expenditure type, education level, card type, and chip used.
- visualised revenue by quarters.
- added cards to show important KPIs.
- added slicer to select week.
- used tree map to provide categories (Quarter, gender, card type, income group).
- calculated sum of revenue, total transaction amount and interest earned by customer job.
- Re-used similar visualisations from transactions Report.
- Showed important metrics using cards.
- Visualised weekly performance using line chart.
- visualised revenue by income group, marital status, and education level.
- identified top performing states using stacked bar chart.
- added new data in both tables to provide real time insights.
- Revenue increased by 28.8%
- Total Transaction Amount increased by 35%
- Overall revenue is 57M
- Total interest is 8M
- Total transaction amount 46M
- Male customers are contributing more in revenue 31M, Female 26M
- Blue and Silver credit cards are contributing to 93% of overall transactions
- TX,NY and CA is contributing to 68%
- Overall activation rate is 57.5%
- Overall delinquent rate is 6.06%