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https://github.com/gakas14/car_insurance_with_aws
Get the dataset intro a S3 bucket, use AWS glue to transform the dataset, write a Lambda script to clean the dataset, query the dataset via AWS Athena then build a dashboard using AWS Quicksight.
https://github.com/gakas14/car_insurance_with_aws
aws aws-athena aws-glue aws-lambda aws-quicksight s3-bucket
Last synced: 8 days ago
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Get the dataset intro a S3 bucket, use AWS glue to transform the dataset, write a Lambda script to clean the dataset, query the dataset via AWS Athena then build a dashboard using AWS Quicksight.
- Host: GitHub
- URL: https://github.com/gakas14/car_insurance_with_aws
- Owner: gakas14
- Created: 2022-09-30T04:49:53.000Z (about 2 years ago)
- Default Branch: main
- Last Pushed: 2022-10-09T09:05:17.000Z (about 2 years ago)
- Last Synced: 2023-11-28T06:30:04.977Z (12 months ago)
- Topics: aws, aws-athena, aws-glue, aws-lambda, aws-quicksight, s3-bucket
- Language: Python
- Homepage:
- Size: 1.11 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Car Insurance with AWS
Objective: To use the Amazon S3, AWS Glue,AWS Lambda, AWS Athena and AWS Quicksight for data engineering and analysis of car insurance, share patterns, and actionable insights.
Problem Statement:
A car insurance company wants to look at its historical data to understand and predict the probability of a customer making a claim based on multiple features other than MVR_POINTS. The data set comprises of 10K plus submitted claim records 14 plus features. The scope of this project is limited to data engineering and analysis.
THIS DASHBORD AWSWER FOLLOW QUESTIONS:
- Count of car by type.
- Customers claim based on the age category, marital status, gender.
- The relation between car claim, car age, and car usage.
- The top two car types with the maximum claim amounts.
