Orchestrate an ETL Pipeline you own this product

prerequisites
Familiarity with AWS services and console • Knowledge of the Python programming language • Basic understanding of AWS Step Functions and their usage in orchestrating data pipelines • Basic understanding of AWS Glue workflows and their usage in data processing pipelines • Familiarity with AWS CloudWatch and its usage in monitoring data pipelines.
skills learned
Using AWS Step Functions and AWS Glue workflows to orchestrate data pipelines • Automating infrastructure using CloudFormation • Monitoring data in a data pipeline.
Gianluigi Mucciolo
1 week · 4-6 hours per week · INTERMEDIATE
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Look inside

Nextstellar Corp needs you to tackle a big challenge: completing their cloud migration by rebuilding their historical data lake as a data layer in the cloud. You’ll implement an effective and automated data orchestration framework for the ingestion and transform and curate layers, using best practices for Infrastructure-as-Code to automate your data layer. Finally, you’ll establish a monitoring system that will automatically alert you to any issues or problems that might crop up.

This project is designed for learning purposes and is not a complete, production-ready application or solution.

project author

Gianluigi Mucciolo
Gianluigi Mucciolo specializes in AWS technologies and Agile methodologies. As an AWS Authorized Instructor and Cloud Technical Principal, he is dedicated to advancing cloud professionals' knowledge and participates in community-building initiatives. With a strong background in Artificial Intelligence and Big Data, Gianluigi constantly seeks growth opportunities.

prerequisites

This liveProject is for engineers who want to build a data lake lambda architecture using AWS fully managed services. You will need to know:


TOOLS
  • Basics of the Linux console
  • Basics of AWS
  • Basics of the AWS console
  • Basics of the AWS CLI

TECHNIQUES
  • Basics of infrastructure automation
  • Basics of big data Lambda architecture

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