📌 Project Overview

This project demonstrates an end-to-end data analytics workflow applied to insurance policy data. The objective was to transform raw structured data into meaningful business insights through data cleaning, SQL integration, KPI development, and interactive dashboard visualization.

The analysis focuses on policy performance, customer demographics, premium growth trends, claims analysis, and payment tracking.

🛠️ Tools & Technologies

Excel – Data cleaning, preprocessing, pivot tables, initial dashboard

MySQL – Database creation, schema design, joins, aggregations

Tableau – Interactive dashboards, calculated fields, filtering

Power BI – Data modeling, DAX measures, KPI visualization

🔄 Technical Workflow

1️⃣ Data Preparation (Excel)

Cleaned and structured raw datasets

Standardized columns and handled missing values

Built initial KPI dashboard using pivot tables

2️⃣ Database Integration (MySQL)

Imported datasets into relational schema

Performed joins across policy, customer, and claims tables

Created aggregated queries for KPI validation

3️⃣ Data Modeling (Power BI & Tableau)

Built relationships between tables

Created calculated measures (DAX & calculated fields)

Designed reusable KPI metrics

4️⃣ Dashboard Development

Interactive filters and slicers

Drill-down capability

Dynamic KPI cards

Trend analysis visualizations

5️⃣ Quality Assurance

Cross-validated SQL outputs with BI dashboards

Ensured metric consistency and data accuracy

📊 Key Performance Indicators (KPIs)

📌 Total Policies

👥 Total Customers

📈 Premium Growth Rate

💰 Total Claim Amount

📝 Claim Status Distribution

💳 Payment Status Analysis

🎯 Age & Gender-based Policy Distribution

⏳ Policies Expiring This Year

📈 Key Insights Generated

Identified demographic trends in policy adoption

Tracked revenue growth through premium analysis

Evaluated claim volume and financial exposure

Highlighted renewal opportunities

Monitored payment compliance patterns