Data lake project for a US based Insurance Company

Project that incorporates TerraForm to create AWS infrastructure using S3, Lambda, and DynamoDB tables for ocean and river data 🐢

Access logs for ELB

Create terraform module for AWS Glue

This project focuses on maintaining data quality and consistency across different data sources. This project features AWS Glue for data cataloging and ETL, AWS DataBrew for visual data preparation, Amazon Redshift for high-quality data storage and analysis, and Amazon RDS for ensuring relational database integrity.

AWS Comprehend is an event-driven, serverless data processing pipeline that leverages AWS services to perform natural language processing and analysis on user-submitted text files.

Glue ETL crawler and jobs with Athena queries

This project demonstrates the integration of data from multiple sources into a unified data lake. The project showcases the use of AWS Glue for ETL tasks, Amazon S3 as a data lake, AWS Data Pipeline for data movement automation, Amazon RDS for relational data storage, and Amazon Redshift for data warehousing and analysis.

These Terraform modules aggregate the AWS Trusted Advisor results from different accounts to a centralised account, using AWS Lambda, AWS IAM, Amazon S3 and Amazon SQS

Companion repository for the "Streamlining AWS Glue CI/CD — A Comprehensive Blueprint" blog post

AWS ETL example via AWS DMS & AWS Glue

These Terraform modules aggregate Security Hub findings to centralized account using Amazon Kinesis Firehose and AWS Glue

Proof of Value Terraform Scripts to utilize Amazon Web Services (AWS) Security, Identity & Compliance Services to Support your AWS Account Security Posture.

Terraform module which creates Glue resources on AWS

Terraform modules for provisioning and managing AWS Glue resources