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https://github.com/greatwoman23/car_insurance_analysis

The Car Insurance Analysis project aims to provide a comprehensive examination of a car insurance portfolio using advanced data analytics tools. The analysis offers valuable insights into policy demographics, claims patterns, and financial metrics, helping stakeholders make informed decisions.
https://github.com/greatwoman23/car_insurance_analysis

bigquery data data-science dataanalytics insurance-claims looker-studio tableau

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The Car Insurance Analysis project aims to provide a comprehensive examination of a car insurance portfolio using advanced data analytics tools. The analysis offers valuable insights into policy demographics, claims patterns, and financial metrics, helping stakeholders make informed decisions.

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# Car Insurance Analysis Project

This project involves a comprehensive analysis of a car insurance dataset using multiple tools and technologies, including BigQuery, Looker Studio, and Tableau. The goal is to extract valuable insights from the data to support operational decision-making and upper management strategy.



 Interested in Car Insurance Analysis? Check out my latest blog post on Medium where I explore the comprehensive data behind car insurance trends and insights.



🔗 Read the full blog post here: https://medium.com/@chemistry8526/unlocking-the-power-of-data-comprehensive-car-insurance-analysis-cdc25cd3e31f



# Project Overview

Data Storage and Querying with BigQuery

Operational Reporting with Looker Studio

Executive Dashboard with Tableau



# Project Structure



1. Data Storage and Querying with BigQuery

We utilized Google BigQuery to store and query the car insurance dataset. BigQuery provides a powerful and scalable platform for handling large datasets and performing complex SQL queries.



SQL Scripts: The bigquery/queries directory contains SQL scripts used for data cleaning, aggregation, and analysis.

Setup Instructions: Detailed instructions for setting up BigQuery and running the queries are provided in bigquery_setup.md.



2. Operational Reporting with Looker Studio

Looker Studio (formerly Google Data Studio) was used to create an operational report that provides detailed insights into the dataset. The report covers policyholder demographics, vehicle information, claims data, income analysis, and geographic distribution.



# Report Highlights:



Age, gender, marital status, and education levels of policyholders.

Distribution of car makes, models, years, and colors.

Total and average claim amounts, claim frequency.

Correlation between household income and claim amounts.

Geographic distribution of claims.



3. Executive Dashboard with Tableau

A dashboard tailored for upper management was created using Tableau. This dashboard presents key metrics and trends in a visually appealing format, allowing for quick and informed decision-making.



# Key Metrics:



Total number of active insurance policies.

Aggregate sum of all claims.

Average claim amount per policy.

Claim frequency per policy.

Average household income of policyholders.



Demographic Insights:



Age, gender, marital status, and education levels of policyholders.



Vehicle Information:



Most common car makes, models, and years.

Claims Analysis:



Claims distribution by coverage zone and car use type.

Breakdown of claim amounts by car make and model.

Correlation between household income and claim amounts.



# Getting Started



Prerequisites

Google Cloud Platform: For using BigQuery.

Looker Studio: For creating and viewing operational reports.

Tableau: For creating and viewing dashboards.



Tableau:



Connect Tableau to the processed data from BigQuery and create the executive dashboard using the provided guidelines.



# Contribution

Feel free to contribute to this project by adding new analyses, improving existing reports, or creating additional visualizations. Please follow the standard GitHub workflow for contributions:



# License

This project is licensed under the MIT License. See the LICENSE file for more details.



# Contact

For any questions or further information, please contact:



Name: Deniran_o

Email: [email protected]