Wow! eBook
Amazon Redshift Cookbook:Recipes for building modern data warehousing solutions
by: Shruti Worlikar (Author), Harshida Patel (Author), Anusha Challa (Author)
Publisher: Packt Publishing
Edition: 2nd ed.
Publication Date: 2025-04-25
Language: English
Print Length: 468 pages
ISBN-10: 1836206917
ISBN-13: 9781836206910
Book Description
Set up a petabyte-scale, cloud-based data warehouse that is burstable and built to scale for end-to-end analytical solutionsKey FeaturesLearn how to translate familiar data warehousing concepts into Redshift implementationUse impressive Redshift features to optimize development, productionizing, and operation processesFind out how to use advanced features such as concurrency scaling, Redshift Spectrum, and federated queriesPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionAmazon Redshift Cookbook offers comprehensive guidance for leveraging AWS's fully managed cloud data warehousing service. Whether you're building new data warehouse workloads or migrating traditional on-premises platforms to the cloud, this essential resource delivers proven implementation strategies. Written by AWS specialists, these easy-to-follow recipes will equip you with the knowledge to successfully implement Amazon Redshift-based data analytics solutions using established best practices.The book focuses on Redshift architecture, showing you how to perform database administration tasks on Redshift. You'll learn how to optimize your data warehouse to quickly execute complex analytic queries against very large datasets. The book covers recipes to help you take full advantage of Redshift's columnar architecture and managed services. You'll discover how to deploy fully automated and highly scalable extract, transform, and load (ETL) processes, helping you minimize the operational effort that you invest in managing regular ETL pipelines and ensuring the timely and accurate refreshing of your data warehouse.By the end of this Redshift book, you'll be able to implement a Redshift-based data analytics solution by adopting best-practice approaches for solving commonly faced problems.What you will learnIntegrate data warehouses with data lakes using AWS featuresCreate end-to-end analytical solutions from sourcing to consumptionUtilize Redshift's security for strict business requirementsApply architectural insights with analytical recipesDiscover big data best practices for managed solutionsEnable data sharing for data mesh and hub-and-spoke architecturesExplore Redshift ML and generative AI with Amazon QWho this book is forThis book is for anyone involved in architecting, implementing, and optimizing an Amazon Redshift data warehouse, including data warehouse developers, data analysts, database administrators, data engineers, and data scientists. Basic knowledge of data warehousing, database systems, as well as cloud concepts and familiarity with Redshift is beneficial.Table of ContentsGetting Started with Amazon RedshiftData ManagementLoading and Unloading DataZero-ETL IngestionsScalable Data Orchestration for AutomationPlatform Authorization and SecurityData Authorization and SecurityPerformance OptimizationCost OptimizationLakehouse ArchitectureData Sharing with Amazon RedshiftGenerative AI and ML with Amazon Redshift
Editorial Reviews
Set up a petabyte-scale, cloud-based data warehouse that is burstable and built to scale for end-to-end analytical solutionsKey FeaturesLearn how to translate familiar data warehousing concepts into Redshift implementationUse impressive Redshift features to optimize development, productionizing, and operation processesFind out how to use advanced features such as concurrency scaling, Redshift Spectrum, and federated queriesPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionAmazon Redshift Cookbook offers comprehensive guidance for leveraging AWS's fully managed cloud data warehousing service. Whether you're building new data warehouse workloads or migrating traditional on-premises platforms to the cloud, this essential resource delivers proven implementation strategies. Written by AWS specialists, these easy-to-follow recipes will equip you with the knowledge to successfully implement Amazon Redshift-based data analytics solutions using established best practices.The book focuses on Redshift architecture, showing you how to perform database administration tasks on Redshift. You'll learn how to optimize your data warehouse to quickly execute complex analytic queries against very large datasets. The book covers recipes to help you take full advantage of Redshift's columnar architecture and managed services. You'll discover how to deploy fully automated and highly scalable extract, transform, and load (ETL) processes, helping you minimize the operational effort that you invest in managing regular ETL pipelines and ensuring the timely and accurate refreshing of your data warehouse.By the end of this Redshift book, you'll be able to implement a Redshift-based data analytics solution by adopting best-practice approaches for solving commonly faced problems.What you will learnIntegrate data warehouses with data lakes using AWS featuresCreate end-to-end analytical solutions from sourcing to consumptionUtilize Redshift's security for strict business requirementsApply architectural insights with analytical recipesDiscover big data best practices for managed solutionsEnable data sharing for data mesh and hub-and-spoke architecturesExplore Redshift ML and generative AI with Amazon QWho this book is forThis book is for anyone involved in architecting, implementing, and optimizing an Amazon Redshift data warehouse, including data warehouse developers, data analysts, database administrators, data engineers, and data scientists. Basic knowledge of data warehousing, database systems, as well as cloud concepts and familiarity with Redshift is beneficial.Table of ContentsGetting Started with Amazon RedshiftData ManagementLoading and Unloading DataZero-ETL IngestionsScalable Data Orchestration for AutomationPlatform Authorization and SecurityData Authorization and SecurityPerformance OptimizationCost OptimizationLakehouse ArchitectureData Sharing with Amazon RedshiftGenerative AI and ML with Amazon Redshift
