5, 10 or 20 seats+ for your team - learn more
As a data engineer for a mobile game development studio, your task is to create a data streaming pipeline that collects and processes large streams of data records in real-time for lightning-fast analytics. Your company’s modern data platform architecture includes an Amazon Athena data lake and an AWS Redshift data warehouse solution. To store files, you’ll create an AWS S3 bucket, and you’ll create an AWS Kinesis delivery stream by using the boto3 library to connect to AWS Kinesis endpoints and send event data to the service. You’ll provision AWS Redshift resources and connect them to your AWS Kinesis Data Stream to analyze user behavior data to understand the user's journey inside the app. When you’re done, you’ll have a simple yet reliable data streaming pipeline that prevents resource shortages and transforms data in real-time—while it’s still relevant—ensuring more accurate data.
This liveProject is for intermediate Python programmers who are interested in creating streaming data pipelines on AWS using Kinesis, Redshift, and CloudFormation. To begin these liveProjects you’ll need to be familiar with the following:
TOOLSgeekle is based on a wordle clone.