Amazon Redshift Cookbook

by Shruti Worlikar
Amazon Redshift Cookbook
Author: Shruti Worlikar
Publisher: Packt Publishing Ltd
Total Pages: 384
Release: 2021-07-23
Genre: Computers
ISBN: 1800561849
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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 FeaturesDiscover how to translate familiar data warehousing concepts into Redshift implementationUse impressive Redshift features to optimize development, productionizing, and operations processesFind out how to use advanced features such as concurrency scaling, Redshift Spectrum, and federated queriesBook Description Amazon 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 learnUse Amazon Redshift to build petabyte-scale data warehouses that are agile at scaleIntegrate your data warehousing solution with a data lake using purpose-built features and services on AWSBuild end-to-end analytical solutions from data sourcing to consumption with the help of useful recipesLeverage Redshift's comprehensive security capabilities to meet the most demanding business requirementsFocus on architectural insights and rationale when using analytical recipesDiscover best practices for working with big data to operate a fully managed solutionWho this book is for This 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.

Amazon Redshift: The Definitive Guide

by Rajesh Francis
Amazon Redshift: The Definitive Guide
Author: Rajesh Francis
Publisher: "O'Reilly Media, Inc."
Total Pages: 465
Release: 2023-10-03
Genre: Computers
ISBN: 109813527X
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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

Redshift

by Al Sarrantonio
Redshift
Author: Al Sarrantonio
Publisher: Roc
Total Pages: 692
Release: 2002
Genre: Fiction
ISBN: 9780451459046
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Thirty works of speculative fiction, including hard and soft science fiction, fantasy, horror, and experimental and conventional literary fiction. These recognized "authors have shaped the evolution of science fiction and will continue to influence the genre for years to come."

Getting Started with Amazon Redshift

by Stefan Bauer
Getting Started with Amazon Redshift
Author: Stefan Bauer
Publisher: Packt Publishing
Total Pages: 154
Release: 2013
Genre: Computers
ISBN: 9781782178088
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Getting Started With Amazon Redshift is a step-by-step, practical guide to the world of Redshift. Learn to load, manage, and query data on Redshift.This book is for CIOs, enterprise architects, developers, and anyone else who needs to get familiar with RedShift. The CIO will gain an understanding of what their technical staff is working on; the technical implementation personnel will get an in-depth view of the technology, and what it will take to implement their own solutions.

Red Shift

by Alan Garner
Red Shift
Author: Alan Garner
Publisher: New York Review of Books
Total Pages: 225
Release: 2011
Genre: Fiction
ISBN: 1590174437
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Three young men from three different time periods influence each other's destiny with the help of a stone axe.

The Mass of Galaxies at Low and High Redshift

by Ralf Bender
The Mass of Galaxies at Low and High Redshift
Author: Ralf Bender
Publisher: Springer Science & Business Media
Total Pages: 394
Release: 2003-01-23
Genre: Science
ISBN: 9783540002055
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Measuring the masses of galaxies as a function of redshift is perhaps one of the most challenging open issues in current astronomical research. The evolution of the baryonic and dark matter components of galaxies is not only a critical test of the hierarchical formation paradigm, but ultimately also provides new clues on the complex interplay between star formation, the cooling and heating of gas and galaxy merging processes. This book reviews current techniques to measure the baryonic (stellar) and dark masses of nearby galaxies, and focusses on ongoing attempts to measure theses same quantities in galaxies at higher and higher redshifts. It also gives room to future perspectives, with special emphasis on new survey projects and satellite missions.

Redshift, Blueshift

by Jordan Silversmith
Redshift, Blueshift
Author: Jordan Silversmith
Publisher: Gival Press
Total Pages: 216
Release: 2021-10
Genre: Fiction
ISBN: 9781940724317
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Winner of the Gival Press Novel Award When a prisoner in an unnamed labor camp finds his journal of memories taken from his cell, he sets out to console himself and perhaps find in his past a way to reclaim his freedom by again writing down what he can remember. As the prisoner writes and passes through the vivid world of a distant life, he is eventually confronted by a strange memory that, if true, questions the reliability of his memories and whether what he remembers was really his own life or, somehow, someone else's.

Pragmatic AI

by Noah Gift
Pragmatic AI
Author: Noah Gift
Publisher: Addison-Wesley Professional
Total Pages: 720
Release: 2018-07-12
Genre: Computers
ISBN: 0134863917
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Master Powerful Off-the-Shelf Business Solutions for AI and Machine Learning Pragmatic AI will help you solve real-world problems with contemporary machine learning, artificial intelligence, and cloud computing tools. Noah Gift demystifies all the concepts and tools you need to get results—even if you don’t have a strong background in math or data science. Gift illuminates powerful off-the-shelf cloud offerings from Amazon, Google, and Microsoft, and demonstrates proven techniques using the Python data science ecosystem. His workflows and examples help you streamline and simplify every step, from deployment to production, and build exceptionally scalable solutions. As you learn how machine language (ML) solutions work, you’ll gain a more intuitive understanding of what you can achieve with them and how to maximize their value. Building on these fundamentals, you’ll walk step-by-step through building cloud-based AI/ML applications to address realistic issues in sports marketing, project management, product pricing, real estate, and beyond. Whether you’re a business professional, decision-maker, student, or programmer, Gift’s expert guidance and wide-ranging case studies will prepare you to solve data science problems in virtually any environment. Get and configure all the tools you’ll need Quickly review all the Python you need to start building machine learning applications Master the AI and ML toolchain and project lifecycle Work with Python data science tools such as IPython, Pandas, Numpy, Juypter Notebook, and Sklearn Incorporate a pragmatic feedback loop that continually improves the efficiency of your workflows and systems Develop cloud AI solutions with Google Cloud Platform, including TPU, Colaboratory, and Datalab services Define Amazon Web Services cloud AI workflows, including spot instances, code pipelines, boto, and more Work with Microsoft Azure AI APIs Walk through building six real-world AI applications, from start to finish Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details.

Data Engineering with AWS

by Gareth Eagar
Data Engineering with AWS
Author: Gareth Eagar
Publisher: Packt Publishing Ltd
Total Pages: 637
Release: 2023-10-31
Genre: Computers
ISBN: 1804613134
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Looking to revolutionize your data transformation game with AWS? Look no further! From strong foundations to hands-on building of data engineering pipelines, our expert-led manual has got you covered. Key Features Delve into robust AWS tools for ingesting, transforming, and consuming data, and for orchestrating pipelines Stay up to date with a comprehensive revised chapter on Data Governance Build modern data platforms with a new section covering transactional data lakes and data mesh Book DescriptionThis book, authored by a seasoned Senior Data Architect with 25 years of experience, aims to help you achieve proficiency in using the AWS ecosystem for data engineering. This revised edition provides updates in every chapter to cover the latest AWS services and features, takes a refreshed look at data governance, and includes a brand-new section on building modern data platforms which covers; implementing a data mesh approach, open-table formats (such as Apache Iceberg), and using DataOps for automation and observability. You'll begin by reviewing the key concepts and essential AWS tools in a data engineer's toolkit and getting acquainted with modern data management approaches. You'll then architect a data pipeline, review raw data sources, transform the data, and learn how that transformed data is used by various data consumers. You’ll learn how to ensure strong data governance, and about populating data marts and data warehouses along with how a data lakehouse fits into the picture. After that, you'll be introduced to AWS tools for analyzing data, including those for ad-hoc SQL queries and creating visualizations. Then, you'll explore how the power of machine learning and artificial intelligence can be used to draw new insights from data. In the final chapters, you'll discover transactional data lakes, data meshes, and how to build a cutting-edge data platform on AWS. By the end of this AWS book, you'll be able to execute data engineering tasks and implement a data pipeline on AWS like a pro!What you will learn Seamlessly ingest streaming data with Amazon Kinesis Data Firehose Optimize, denormalize, and join datasets with AWS Glue Studio Use Amazon S3 events to trigger a Lambda process to transform a file Load data into a Redshift data warehouse and run queries with ease Visualize and explore data using Amazon QuickSight Extract sentiment data from a dataset using Amazon Comprehend Build transactional data lakes using Apache Iceberg with Amazon Athena Learn how a data mesh approach can be implemented on AWS Who this book is forThis book is for data engineers, data analysts, and data architects who are new to AWS and looking to extend their skills to the AWS cloud. Anyone new to data engineering who wants to learn about the foundational concepts, while gaining practical experience with common data engineering services on AWS, will also find this book useful. A basic understanding of big data-related topics and Python coding will help you get the most out of this book, but it’s not a prerequisite. Familiarity with the AWS console and core services will also help you follow along.