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https://github.com/dharmendradiwaker/eda-insurance-policies-by-tableau

Exploratory-Data-Analysis-of-Insurance-Policies-using-Tableau Loaded, cleaned & analyzed Insurance data for 37.5K+ policy containing 16 columns Created visualizations such as Area chart, stacked bar charts, lines charts etc. for insights
https://github.com/dharmendradiwaker/eda-insurance-policies-by-tableau

data-visualization eda tableau

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Exploratory-Data-Analysis-of-Insurance-Policies-using-Tableau Loaded, cleaned & analyzed Insurance data for 37.5K+ policy containing 16 columns Created visualizations such as Area chart, stacked bar charts, lines charts etc. for insights

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# 📊 Exploratory Data Analysis of Insurance Policies using Tableau



This project focuses on analyzing a dataset of **37.5K+ insurance policies** to uncover insights into the trends, behaviors, and patterns of policyholders. The data includes **16 columns**, containing information about the policyholders and the insurance policies they have taken.



Using **Tableau**, I performed data cleaning, exploration, and created a series of **visualizations** to help gain deeper insights into the insurance industry.



## 🧑‍💼 Project Overview



The goal of this project was to explore the relationships and patterns within the data to provide a better understanding of the insurance policies taken by individuals. By visualizing key variables, we can uncover trends and make informed decisions.



## 📊 Key Steps Taken



### 1. **Data Loading and Cleaning** 🧹

   - Loaded the **insurance data** containing **37.5K+ policies** with **16 columns**.

   - Cleaned the data by removing any inconsistencies or missing values to ensure accuracy in the analysis.



### 2. **Data Analysis and Insights** 🔍

   - Performed **Exploratory Data Analysis (EDA)** using Tableau to uncover meaningful patterns and relationships.

   - Analyzed variables such as policyholder demographics, policy types, and claim history to gain valuable insights.



### 3. **Visualizations Created** 🎨

   - Used various **visualization techniques** in Tableau to present insights clearly and intuitively:

     - **Area Charts**: To show the trends and distribution of policies over time.

     - **Stacked Bar Charts**: To represent multiple categories, such as policy types and regions.

     - **Line Charts**: To analyze trends over periods and compare variables.

   - **Key Findings**:

     - People with **bachelor's degrees** were found to be taking more policies compared to other educational backgrounds.



## 📈 Key Insights



- **Education and Policy Ownership** 🎓: 

   - Policyholders with **bachelor’s degrees** tend to take more policies compared to those with other education levels. This could indicate a higher awareness or financial stability among people with higher education.



- **Policy Trends** 📅: 

   - The area charts and line charts highlighted **seasonal trends** in the uptake of insurance policies, helping understand which periods are more favorable for the insurance industry.



- **Demographic Insights** 🏙️:

   - The stacked bar charts revealed trends across different regions, age groups, and genders, giving a deeper understanding of the customer base.



## 🛠️ Tools and Technologies Used



- **Tableau** 🖥️: Used for **data cleaning**, **visualization**, and **insight generation**.



## 🚀 Getting Started



1. **Clone the repository**:

   ```bash

   git clone https://github.com/dharmendradiwaker/EDA-Insurance-Policies-By-Tableau.git

   ```



2. **Open the Tableau file**:

   - Open the Tableau workbook (e.g., `Insurance_Policies_Analysis.twb`) to explore the interactive visualizations.



3. **Insights Exploration**:

   - Explore the visualizations to uncover trends in the insurance policies based on various factors like **education**, **age**, **region**, and more.