Welcome to Data_Engineering_in_AWS, a one-stop repository for all things related to Data Engineering in the AWS ecosystem. Whether you are a beginner looking for tutorials or an expert in need of advanced topics, this repository has something to offer. It covers a wide range of AWS services and tools including AWS Glue, Lambda, S3, Athena, Kinesis, EMR, and many more.
- ETL Pipeline Templates: Reusable ETL pipeline templates using AWS Glue and Lambda.
- Serverless Data Lake: Set up a serverless data lake using AWS S3 and Athena.
- Real-Time Data Processing: Examples for setting up real-time data processing systems.
- Big Data Analysis: Utilize EMR for big data analytics tasks.
- Monitoring and Logging: Leverage AWS CloudWatch for pipeline monitoring.
- ... and many more!
Before diving into this repository, you should have:
- An AWS Account
- Basic understanding of AWS services
- Familiarity with Data Engineering concepts
Clone this repository into your local machine to explore further:
git clone https://github.com/YourUsername/Data_Engineering_in_AWS.gitStep-by-step tutorials for complex scenarios are available here.
If you want to get up and running quickly, check out our Quick Start Guides.
Detailed information about each project component is available in the respective directories:
I love contributions! Please see our Contributing Guidelines for more details.
This project is licensed under the Apache License 2.0. See the LICENSE file for details.