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Amazon Redshift Cookbook - Second Edition

Amazon Redshift Cookbook provides practical techniques for utilizing AWS's managed data warehousing service effectively. With this book, you'll learn to create scalable and secure data analytics solutions, tackle data integration challenges, and leverage Redshift's advanced features like data sharing and generative AI capabilities. What this Book will help me do Create end-to-end data analytics solutions from ingestion to reporting using Amazon Redshift. Optimize the performance and security of Redshift implementations to meet enterprise standards. Leverage Amazon Redshift for zero-ETL ingestion and advanced concurrency scaling. Integrate Redshift with data lakes for enhanced data processing versatility. Implement generative AI and machine learning solutions directly within Redshift environments. Author(s) Shruti Worlikar, Harshida Patel, and Anusha Challa are seasoned data experts who bring together years of experience with Amazon Web Services and data analytics. Their combined expertise enables them to offer actionable insights, hands-on recipes, and proven strategies for implementing and optimizing Amazon Redshift-based solutions. Who is it for? This book is best suited for data analysts, data engineers, and architects who are keen on mastering modern data warehouse solutions using Redshift. Readers should have some knowledge of data warehousing and familiarity with cloud concepts. Ideal for professionals looking to migrate on-premises systems or build cloud-native analytics pipelines leveraging Redshift.

Amazon Redshift: The Definitive Guide

Amazon Redshift powers analytic cloud data warehouses worldwide, from startups to some of the largest enterprise data warehouses available today. This practical guide thoroughly examines this managed service and demonstrates how you can use it to extract value from your data immediately, rather than go through the heavy lifting required to run a typical data warehouse. Analytic specialists Rajesh Francis, Rajiv Gupta, and Milind Oke detail Amazon Redshift's underlying mechanisms and options to help you explore out-of-the box automation. Whether you're a data engineer who wants to learn the art of the possible or a DBA looking to take advantage of machine learning-based auto-tuning, this book helps you get the most value from Amazon Redshift. By understanding Amazon Redshift features, you'll achieve excellent analytic performance at the best price, with the least effort. This book helps you: Build a cloud data strategy around Amazon Redshift as foundational data warehouse Get started with Amazon Redshift with simple-to-use data models and design best practices Understand how and when to use Redshift Serverless and Redshift provisioned clusters Take advantage of auto-tuning options inherent in Amazon Redshift and understand manual tuning options Transform your data platform for predictive analytics using Redshift ML and break silos using data sharing Learn best practices for security, monitoring, resilience, and disaster recovery Leverage Amazon Redshift integration with other AWS services to unlock additional value

Serverless Machine Learning with Amazon Redshift ML

Serverless Machine Learning with Amazon Redshift ML provides a hands-on guide to using Amazon Redshift Serverless and Redshift ML for building and deploying machine learning models. Through SQL-focused examples and practical walkthroughs, you will learn efficient techniques for cloud data analytics and serverless machine learning. What this Book will help me do Grasp the workflow of building machine learning models with Redshift ML using SQL. Learn to handle supervised learning tasks like classification and regression. Apply unsupervised learning techniques, such as K-means clustering, in Redshift ML. Develop time-series forecasting models within Amazon Redshift. Understand how to operationalize machine learning in serverless cloud architecture. Author(s) Debu Panda, Phil Bates, Bhanu Pittampally, and Sumeet Joshi are seasoned professionals in cloud computing and machine learning technologies. They combine deep technical knowledge with teaching expertise to guide learners through mastering Amazon Redshift ML. Their collaborative approach ensures that the content is accessible, engaging, and practically applicable. Who is it for? This book is perfect for data scientists, machine learning engineers, and database administrators using or intending to use Amazon Redshift. It's tailored for professionals with basic knowledge of machine learning and SQL who aim to enhance their efficiency and specialize in serverless machine learning within cloud architectures.

Amazon Redshift Cookbook

Dive into the world of Amazon Redshift with this comprehensive cookbook, packed with practical recipes to build, optimize, and manage modern data warehousing solutions. From understanding Redshift's architecture to implementing advanced data warehousing techniques, this book provides actionable guidance to harness the power of Amazon Redshift effectively. What this Book will help me do Master the architecture and core concepts of Amazon Redshift to architect scalable data warehouses. Optimize data pipelines and automate ETL processes for seamless data ingestion and management. Leverage advanced features like concurrency scaling and Redshift Spectrum for enhanced analytics. Apply best practices for security and cost optimization in Redshift projects. Gain expertise in scaling data warehouse solutions to accommodate large-scale analytics needs. Author(s) Shruti Worlikar, None Arumugam, and None Patel are seasoned experts in data warehousing and analytics with extensive experience using Amazon Redshift. Their backgrounds in implementing scalable data solutions make their insights practical and grounded. Through their collaborative writing, they aim to make complex topics approachable to learners of various skill levels. Who is it for? This book is tailored for professionals such as data warehouse developers, data engineers, and data analysts looking to master Amazon Redshift. It suits intermediate to advanced practitioners with a basic understanding of data warehousing and cloud technologies. Readers seeking to optimize Redshift for cost, performance, and security will find this guide invaluable.