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 migrationsKey FeaturesGet up to speed with the different AWS technologies for data engineeringLearn the different aspects and considerations of building data lakes, such as security, storage, and operationsGet hands on with key AWS services such as Glue, EMR, Redshift, QuickSight, and Athena for practical learningPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionPerforming 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 learnDefine your centralized data lake solution, and secure and operate it at scaleIdentify the most suitable AWS solution for your specific needsBuild data pipelines using multiple ETL technologiesDiscover how to handle data orchestration and governanceExplore how to build a high-performing data serving layerDelve into DevOps and data quality best practicesMigrate your data from on-premises to AWSWho 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 ContentsManaging Data Lake StorageSharing Your Data Across Environments and AccountsIngesting and Transforming Your Data with AWS GlueA Deep Dive into AWS Orchestration FrameworksRunning Big Data Workloads with Amazon EMRGoverning Your PlatformData Quality ManagementDevOps – Defining IaC and Building CI/CD PipelinesMonitoring Data Lake Cloud InfrastructureBuilding a Serving Layer with AWS Analytics ServicesMigrating to AWS – Steps, Strategies, and Best Practices for Modernizing Your Analytics and Big Data WorkloadsHarnessing the Power of AWS for Seamless Data Warehouse MigrationStrategizing Hadoop Migrations – Cost, Data, and Workflow Modernization with AWS Read more