Power BI Analysis ( Customer churn ) داش بورد فعالة

انشاء داش بورد احترافية باستخدام power bi tools

- customer churn Analysis project

1. Process Steps

• Data Import : Load the customer dataset (CSV) into Power BI.

• Data Cleaning:

- Handle missing || null values.

- Convert categorical fields .

- Create calculated measures using DAX.

• Data Modeling:

- Create Measures such as:

- Churn Rate = DIVIDE(CALCULATE(COUNTROWS(CustomerTable), CustomerTable[Churn]="Yes"), COUNTROWS(CustomerTable))

- Avg Tenure Retained = AVERAGEX(FILTER(CustomerTable, CustomerTable[Churn]="No"), CustomerTable[tenure])

- Avg Tenure Churned = AVERAGEX(FILTER(CustomerTable, CustomerTable[Churn]="Yes"), CustomerTable[tenure])

• Visualization:

- KPI Cards (Churn Rate, Avg Tenure Retained, Avg Tenure Churned).

- Bar Charts (Churn Rate by Contract, Internet Service).

- Donut Chart (Tenure distribution by Contract Type).

- Line Chart (Churn trend over time).

- Matrix (Churn by Gender, Dependents, Partner).

2. Key Findings

• Month-to-Month contract customers show the highest churn rate.

• Fiber optic internet service customers have significantly higher churn.

• Two-Year contract customers show the lowest churn rate.

• The average tenure of retained customers is almost double that of churned customers.

• Churn trends show gradual increases between 2018 and 2024.