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Amazon Redshift Cookbook

Recipes for building modern data warehousing solutions

; Thiyagarajan Arumugam ; Harshida Patel ; Eugene Kawamoto

Discover how to build a cloud-based data warehouse at petabyte-scale that is burstable and built to scale for end-to-end analytical solutions

Key Features

Discover how to translate familiar data warehousing concepts into Redshift implementation
Use impressive Redshift features to optimize development, productionizing, and operations processes
Find out how to use advanced features such as concurrency scaling, Redshift Spectrum, and federated queries

Book DescriptionAmazon Redshift is a fully managed, petabyte-scale AWS cloud data warehousing service. Les mer
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641,-

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Leveringstid: Sendes innen 21 dager

Paperback
Legg i
Paperback
Legg i
Vår pris: 641,-

(Paperback) Fri frakt!
Leveringstid: Sendes innen 21 dager

Om boka

Discover how to build a cloud-based data warehouse at petabyte-scale that is burstable and built to scale for end-to-end analytical solutions

Key Features

Discover how to translate familiar data warehousing concepts into Redshift implementation
Use impressive Redshift features to optimize development, productionizing, and operations processes
Find out how to use advanced features such as concurrency scaling, Redshift Spectrum, and federated queries

Book DescriptionAmazon Redshift is a fully managed, petabyte-scale AWS cloud data warehousing service. It enables you to build new data warehouse workloads on AWS and migrate on-premises traditional data warehousing platforms to Redshift.

This book on Amazon Redshift starts by focusing on Redshift architecture, showing you how to perform database administration tasks on Redshift. You'll then learn how to optimize your data warehouse to quickly execute complex analytic queries against very large datasets. Because of the massive amount of data involved in data warehousing, designing your database for analytical processing lets you take full advantage of Redshift's columnar architecture and managed services. As you advance, you'll discover how to deploy fully automated and highly scalable extract, transform, and load (ETL) processes, which help minimize the operational efforts that you have to invest in managing regular ETL pipelines and ensure the timely and accurate refreshing of your data warehouse. Finally, you'll gain a clear understanding of Redshift use cases, data ingestion, data management, security, and scaling so that you can build a scalable data warehouse platform.

By the end of this Redshift book, you'll be able to implement a Redshift-based data analytics solution and have understood the best practice solutions to commonly faced problems.

What you will learn

Use Amazon Redshift to build petabyte-scale data warehouses that are agile at scale
Integrate your data warehousing solution with a data lake using purpose-built features and services on AWS
Build end-to-end analytical solutions from data sourcing to consumption with the help of useful recipes
Leverage Redshift's comprehensive security capabilities to meet the most demanding business requirements
Focus on architectural insights and rationale when using analytical recipes
Discover best practices for working with big data to operate a fully managed solution

Who this book is forThis book is for anyone involved in architecting, implementing, and optimizing an Amazon Redshift data warehouse, such as data warehouse developers, data analysts, database administrators, data engineers, and data scientists. Basic knowledge of data warehousing, database systems, and cloud concepts and familiarity with Redshift will be beneficial.

Fakta

Innholdsfortegnelse

Table of Contents

Getting Started with Amazon Redshift
Data Management
Loading & Unloading data
Data Pipelines
Scalable Data Orchestration for Automation
Data Authorization & Security
Performance Optimization
Cost Optimization
Lake House Architecture
Extending Redshift Capabilities

Om forfatteren

Shruti Worlikar is a cloud professional with technical expertise in data lakes and analytics across cloud platforms. Her background has led her to become an expert in on-premises-to-cloud migrations and building cloud-based scalable analytics applications. Shruti earned her bachelor's degree in electronics and telecommunications from Mumbai University in 2009 and later earned her masters' degree in telecommunications and network management from Syracuse University in 2011. Her work history includes work at J.P. Morgan Chase, MicroStrategy, and Amazon Web Services (AWS). She is currently working in the role of Manager, Analytics Specialist SA at AWS, helping customers to solve real-world analytics business challenges with cloud solutions and working with service teams to deliver real value. Shruti is the DC Chapter Director for the non-profit Women in Big Data (WiBD) and engages with chapter members to build technical and business skills to support their career advancements. Originally from Mumbai, India, Shruti currently resides in Aldie, VA, with her husband and two kids.
Thiyagarajan Arumugam (Thiyagu) is a principal big data solution architect at AWS, architecting and building solutions at scale using big data to enable data-driven decisions. Prior to AWS, Thiyagu as a data engineer built big data solutions at Amazon, operating some of the largest data warehouses and migrating to and managing them. He has worked on automated data pipelines and built data lake-based platforms to manage data at scale for the customers of his data science and business analyst teams. Thiyagu is a certified AWS Solution Architect (Professional), earned his master's degree in mechanical engineering at the Indian Institute of Technology, Delhi, and is the author of several blog posts at AWS on big data. Thiyagu enjoys everything outdoors - running, cycling, ultimate frisbee - and is currently learning to play the Indian classical drum the mrudangam. Thiyagu currently resides in Austin, TX, with his wife and two kids.
Harshida Patel is a senior analytics specialist solution architect at AWS, enabling customers to build scalable data lake and data warehousing applications using AWS analytical services. She has presented Amazon Redshift deep-dive sessions at re:Invent. Harshida has a bachelor's degree in electronics engineering and a master's in electrical and telecommunication engineering. She has over 15 years of experience architecting and building end-to-end data pipelines in the data management space. In the past, Harshida has worked in the insurance and telecommunication industries. She enjoys traveling and spending quality time with friends and family, and she lives in Virginia with her husband and son.