Credit Card Transaction Weekly PowerBI Dashboard

Project Objective:

To develop a comprehensive credit card weekly PowerBI dashboard that provides real time insights into key-performance-metrics and trends, enabling stakeholders to monitor and analyze credit card operations iffectively.

Preparing Data:

1. Prepare/Download the given CSV files
2. CREATE TABLES in SQL (MySQL / PostgreSQL)
3. IMPORT CSV File into SQL.

Loading/Importing data from (CSV)/(Excel) to MySQL:

Loading/Importing data from (CSV)/(Excel) to PostgreSQL:

DAX Queries Written:

1. Created (AgeGroup) column in (cust_detail) table

   AgeGroup = SWITCH(
    TRUE(),
    'credit_card_db cust_detail'[Customer_Age] < 30, "20-30",
    'credit_card_db cust_detail'[Customer_Age] >= 30 && 'credit_card_db cust_detail'[Customer_Age] < 40, "30-40",
    'credit_card_db cust_detail'[Customer_Age] >= 40 && 'credit_card_db cust_detail'[Customer_Age] < 50, "40-50",
    'credit_card_db cust_detail'[Customer_Age] >= 50 && 'credit_card_db cust_detail'[Customer_Age] < 60, "50-60",
    'credit_card_db cust_detail'[Customer_Age] >= 60, "60+",
    "unknown"
   )
   

2. Created (IncomeGroup) column in (cust_detail) table

   IncomeGroup = SWITCH(
    TRUE(),
    'credit_card_db cust_detail'[Income] < 35000, "Low",
    'credit_card_db cust_detail'[Income] >= 35000 && 'credit_card_db cust_detail'[Income] < 70000, "Med",
    'credit_card_db cust_detail'[Income] >= 70000, "High",
    "unknown"
   )
   

3. Created (week_num2) column in (cc_detail) table, for to get sorted whole number for original (week_num) column
   week_num2 = WEEKNUM('credit_card_db cc_detail'[Week_Start_Date])

4. Created (Revenue) column in (cc_detail) table
   Revenue = 'credit_card_db cc_detail'[Annual_Fees] + 'credit_card_db cc_detail'[Total_Trans_Amt] + 'credit_card_db cc_detail'[Interest_Earned]

5. Created (Current_Week_Revenue) and (Previous_Week_Revenue) MEASURE in (cc_detail) table

   Current_Week_Revenue = CALCULATE(
    SUM('credit_card_db cc_detail'[Revenue]),
    FILTER(
        ALL('credit_card_db cc_detail'),
        'credit_card_db cc_detail'[week_num2] = MAX('credit_card_db cc_detail'[week_num2])))
   

   Previous_Week_Revenue = CALCULATE(
    SUM('credit_card_db cc_detail'[Revenue]),
    FILTER(
        ALL('credit_card_db cc_detail'),
        'credit_card_db cc_detail'[week_num2] = MAX('credit_card_db cc_detail'[week_num2])-1))
   

TOP 10 Project Insights:

1. Revenue Increased by around 28.8% ($55M to $57M) in last 53th week (clearly visible from below chart

2. Total Transaction Amount Increased from $45M -> $46M

3. Total Interest Earned Increased from $7.8M -> $8.0M

4. Male Customers are contributing more in Revenue in comparision to Female customers
   

5. Blue and Silver Card Holder Customers Contributing to 93% of overall transactions
   

6. TX(Texas), NY(New York) and CA(California) states are contributing 72% of overall transactions
   

7. Overall Activation Rate is 57.5%

8. Overall Delinquent Rate(the amount of debt/loan that is past due, i.e customers who are unable to pay their loan) is 6.06%

9. Customers who are graduated have contributed $22M / $55M = 40% of overall transactions
   

10. Similary customers who are businessman have contributed $17.4M / $55M = 31.6% of overall transactions