1. Abstract

In today’s competitive business environment, retaining customers is very important for companies. Customer churn refers to the rate at which customers stop doing business with an organization over a given period of time. High churn rates can lead to loss of revenue and reduced business growth.

This project focuses on analyzing customer churn using Power BI. The data is collected from multiple sources such as Excel and CSV files. The dataset contains customer details like credit score, age, geography, gender, balance, and activity status.

Exploratory Data Analysis is performed to understand customer behavior. Relationships between different factors and churn are analyzed using interactive dashboards. This project helps businesses identify churn patterns and take preventive actions.

2. Objectives

The main objectives of this project are:

1. To understand the concept of customer churn.
2. To analyze customer data using Power BI.
3. To import data from Excel and CSV sources.
4. To study fact and dimension tables.
5. To create relationships between tables.
6. To perform data cleaning and transformation.
7. To build interactive dashboards.
8. To identify factors affecting customer churn.
9. To improve business decision-making.
10. To enhance data visualization skills.

3. Existing System

In the existing system, customer churn analysis is mostly done using manual methods and basic reports.

The limitations of the existing system are:

1. Manual data analysis.
2. Time-consuming reporting process.
3. Limited visualization options.
4. No real-time insights.
5. Difficulty in handling large datasets.
6. Poor data integration.
7. Less accurate predictions.

These limitations reduce business efficiency and decision-making quality.

4. Proposed System

The proposed system uses Power BI for advanced customer churn analysis.

In this system:

• Data is imported from Excel and CSV files.

• Fact and dimension tables are created.

• Relationships are built using model view.

• Data is transformed using Power Query.

• Interactive dashboards are designed.

• Filters and slicers are applied.

• Churn patterns are analyzed.

• Business insights are generated.

This system provides better visualization and accurate churn analysis.

5. Implementation Procedure

The project is implemented using the following steps:

Step 1: Data Collection

Customer data is collected from Excel and CSV files.

Step 2: Data Import

Data is imported into Power BI using import mode.

Step 3: Data Modeling

Fact and dimension tables are created and connected.

Step 4: Data Cleaning

• Removing duplicates

• Handling missing values

• Formatting columns

• Renaming fields

Step 5: Exploratory Data Analysis

Charts and summaries are created to study data trends.

Step 6: Relationship Building

Tables are connected using primary and foreign keys.

Step 7: Dashboard Creation

Interactive reports are designed using visuals.

Step 8: Analysis and Reporting

Churn insights are generated and presented.

6. Software Requirements

The software tools required for this project are:

• Microsoft Power BI

• Microsoft Excel

• CSV File Reader

• Windows Operating System

• Web Browser

• SQL Server (Optional)

• Azure Database (Optional)

7. Hardware Requirements

The hardware requirements include:

• Processor: Intel i5 or higher

• RAM: 8 GB or higher

• Storage: 256 GB or higher

• System: Laptop/Desktop

• Internet Connection: Stable broadband

Optional:

• Cloud system for database hosting

8. Advantages of the Project

1. Helps identify customer churn patterns.
2. Improves customer retention strategies.
3. Saves time in data analysis.
4. Provides interactive dashboards.
5. Supports large datasets.
6. Enhances business decision-making.
7. Improves visualization skills.
8. Easy to understand reports.
9. Can be used in banking and telecom sectors.
10. Useful for management planning.