Amazon Redshift Cookbook: Recipes for building modern data warehousing solutions - Tapa blanda

Sinopsis

Set up a petabyte-scale, cloud-based data warehouse that is burstable and built to scale for end-to-end analytical solutions

Key Features

• Learn how to translate familiar data warehousing concepts into Redshift implementation
• Use impressive Redshift features to optimize development, productionizing, and operation processes
• Find out how to use advanced features such as concurrency scaling, Redshift Spectrum, and federated queries
• Purchase of the print or Kindle book includes a free PDF eBook

Book Description

Amazon 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 learn

• Integrate data warehouses with data lakes using AWS features
• Create end-to-end analytical solutions from sourcing to consumption
• Utilize Redshift's security for strict business requirements
• Apply architectural insights with analytical recipes
• Discover big data best practices for managed solutions
• Enable data sharing for data mesh and hub-and-spoke architectures
• Explore Redshift ML and generative AI with Amazon Q

Who this book is for

This 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 Contents

1. Getting Started with Amazon Redshift
2. Data Management
3. Loading and Unloading Data
4. Zero-ETL Ingestions
5. Scalable Data Orchestration for Automation
6. Platform Authorization and Security
7. Data Authorization and Security
8. Performance Optimization
9. Cost Optimization
10. Lakehouse Architecture
11. Data Sharing with Amazon Redshift
12. Generative AI and ML with Amazon Redshift

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