Data Engineering on AWS - The Complete Training: Design, Build, and Scale End-to-End Data Pipelines with the AWS Analytics Ecosystem

Ashish Prajapati

AU$38.99

Video Jul 2025 18hrs 56mins 1st Edition

Renews at AU$24.99p/m

Ashish Prajapati

AU$38.99

Video Jul 2025 18hrs 56mins 1st Edition

Renews at AU$24.99p/m

Renews at AU$24.99p/m

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Key benefits

End-to-end coverage of AWS data engineering tools and services
Real-world pipeline building across batch, streaming, and big data workloads
Integration of analytics, orchestration, and migration workflows in AWS

Description

This course begins by laying the foundation of data analytics and introducing AWS data engineering services. You’ll start with AWS Glue, learning to catalog, transform, and manage data using workflows, job bookmarks, and quality checks, followed by visual data preparation with Glue Databrew. Next, you’ll move into data warehousing with Amazon Redshift, from cluster creation to serverless deployment and performance tuning. As the journey continues, the focus shifts to real-time data processing with Amazon Kinesis and MSK, covering stream management, Flink applications, and Kafka integration. You’ll then explore big data processing using Amazon EMR, understanding MapReduce, Spark, and cost-effective serverless execution. The course then guides you through building data lakes using AWS Lake Formation and querying them efficiently with Amazon Athena. In the final stages, you’ll visualize data using Amazon QuickSight and orchestrate pipelines through Step Functions and AppFlow. You’ll also gain experience with AWS data migration tools like DMS and DataSync. The course concludes with extended AWS services including Lambda, S3, EC2, and DynamoDB, empowering you to design and manage complete, scalable data platforms in the cloud.

Who is this book for?

This course is designed for aspiring data engineers, cloud engineers, and developers who wish to deepen their expertise in AWS-based data architecture. Prerequisites include basic knowledge of cloud computing, databases, and programming (preferably Python or SQL). Familiarity with AWS services is helpful but not mandatory.