In this hands-on lab, you will learn how to implement a real-time data-processing pipeline using Amazon Kinesis. You will ingest streaming data using Amazon Kinesis Data Streams, process these streams using AWS Lambda and Amazon Kinesis Data Analytics, and deliver the processed data to Amazon S3 for storage. This lab will demonstrate the practical aspects of setting up a real-time data pipeline that can handle large volumes of data in a business scenario, enabling you to respond to changes in real-time and make data-driven decisions quickly. The lab covers key concepts of data ingestion, processing, and storage in a serverless architecture. You will also learn how to ensure data quality throughout the data processing pipeline. Upon completion of this lab, you should have a strong understanding of how to manage a real-time streaming data pipeline on AWS and be prepared for associate-level AWS certification topics involving data engineering with real-time feeds.
A retail company wants to monitor customer interactions on their e-commerce site in real-time to enhance user experience and improve sales. The company needs a reliable, scalable data pipeline that can capture and analyze customer events as they occur. Your task is to build a real-time data processing pipeline using Amazon Kinesis Data Streams for capturing data, AWS Lambda functions for processing the incoming streams, and storing the results in Amazon S3 for further analysis.
