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

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 like Glue, EMR, Redshift, Athena, and QuickSight for practical learning Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionPerforming data engineering with Amazon Web Services 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 like Glue, EMR, Redshift, Athena, and QuickSight. Additionally, you’ll explore data governance, DevOps, CI/CD, and Infrastructure as Code. As you progress, you’ll also gain insights into Tableau Server and Cloud.By the end of this book, you’ll be well-versed in AWS data engineering and have gained proficiency in key AWS services, mastered data processing techniques, and developed the skills necessary 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-premise to AWS Who this book is forIf you're involved in designing, building, or overseeing data solutions on AWS, this book provides proven strategies for addressing challenges in large-scale data environments. Data engineers as well as big data professionals looking to enhance their understanding of AWS features for optimizing their workflow, even if they're new to the platform, will find value. Basic familiarity with AWS security (users and roles) and command shell is recommended. Table of Contents Managing Data Lake Storage Sharing Your Data Across Environments and Accounts Ingesting and Transforming Your Data with AWS Glue A Deep Dive into AWS Orchestration Frameworks Running Big Data Workloads with Amazon EMR Governing Your Platform Data Quality Management DevOps – Defining IaC and Building CI/CD Pipelines Monitoring Data Lake Cloud Infrastructure Buiding the serving layer on AWS Redshift, Athena and Quicksight On-premise Platform Migration to AWS Security and governance with Google Cloud BigLake