Data Engineering with AWS Cookbook: A recipe-based approach to help you tackle data engineering problems with AWS services

January 5, 2025 Books
Data Engineering with AWS Cookbook: A recipe-based approach to help you tackle data engineering problems with AWS services

English | 2024 | ISBN: 978-1805127284 | 528 Pages | EPUB | 37 MB

Master AWS data engineering services and techniques for orchestrating pipelines, building layers, and managing migrations

Key Features

  • Get up to speed with the different AWS technologies for data engineering
  • Learn the different aspects and considerations of building data lakes, such as security, storage, and operations
  • Get hands on with key AWS services such as Glue, EMR, Redshift, QuickSight, and Athena for practical learning

Performing data engineering with Amazon Web Services (AWS) combines AWS’s scalable infrastructure with robust data processing tools, enabling efficient data pipelines and analytics workflows. This comprehensive guide to AWS data engineering will teach you all you need to know about data lake management, pipeline orchestration, and serving layer construction.

Through clear explanations and hands-on exercises, you’ll master essential AWS services such as Glue, EMR, Redshift, QuickSight, and Athena. Additionally, you’ll explore various data platform topics such as data governance, data quality, DevOps, CI/CD, planning and performing data migration, and creating Infrastructure as Code. As you progress, you will gain insights into how to enrich your platform and use various AWS cloud services such as AWS EventBridge, AWS DataZone, and AWS SCT and DMS to solve data platform challenges.

Each recipe in this book is tailored to a daily challenge that a data engineer team faces while building a cloud platform. By the end of this book, you will be well-versed in AWS data engineering and have gained proficiency in key AWS services and data processing techniques. You will develop the necessary skills to tackle large-scale data challenges with confidence.

What you will learn

  • Define your centralized data lake solution, and secure and operate it at scale
  • Identify the most suitable AWS solution for your specific needs
  • Build data pipelines using multiple ETL technologies
  • Discover how to handle data orchestration and governance
  • Explore how to build a high-performing data serving layer
  • Delve into DevOps and data quality best practices
  • Migrate your data from on-premises to AWS
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