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LEADER 00000cam a2200613 i 4500
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049 INap
082 04 005.745
082 04 005.745|223
099 eBook O'Reilly for Public Libraries
100 1 Worlikar, Shruti,|eauthor.
245 10 Amazon redshift cookbook :|brecipes for building modern
data warehousing solutions /|cShruti Worlikar,
Thiyagarajan Arumugam, Harshida Patel.|h[O'Reilly
electronic resource]
264 1 Birmingham :|bPackt Publishing, Limited,|c2021.
300 1 online resource
336 text|btxt|2rdacontent
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505 0 Cover -- Title Page -- Copyright and Credits --
Contributors -- Table of Contents -- Preface -- Chapter 1:
Getting Started with Amazon Redshift -- Technical
requirements -- Creating an Amazon Redshift cluster using
the AWS Console -- Getting ready -- How to do it ... --
Creating an Amazon Redshift cluster using the AWS CLI --
Getting ready -- How to do it ... -- How it works ... --
Creating an Amazon Redshift cluster using an AWS
CloudFormation template -- Getting ready -- How to do it
... -- How it works ... -- Connecting to an Amazon
Redshift cluster using the Query Editor -- Getting ready
505 8 How to do it ... -- Connecting to an Amazon Redshift
cluster using the SQL Workbench/J client -- Getting ready
-- How to do it ... -- Connecting to an Amazon Redshift
Cluster using a Jupyter Notebook -- Getting ready -- How
to do it ... -- Connecting to an Amazon Redshift cluster
using Python -- Getting ready -- How to do it ... --
Connecting to an Amazon Redshift cluster programmatically
using Java -- Getting ready -- How to do it ... --
Connecting to an Amazon Redshift cluster programmatically
using .NET -- Getting ready -- How to do it ... --
Connecting to an Amazon Redshift cluster using the command
line
505 8 Getting ready -- How to do it ... -- Chapter 2: Data
Management -- Technical requirements -- Managing a
database in an Amazon Redshift cluster -- Getting ready --
How to do it ... -- Managing a schema in a database --
Getting ready -- How to do it ... -- Managing tables --
Getting ready -- How to do it ... -- How it works ... --
Managing views -- Getting ready -- How to do it ... --
Managing materialized views -- Getting ready -- How to do
it ... -- How it works ... -- Managing stored procedures -
- Getting ready -- How to do it ... -- How it works ... --
Managing UDFs -- Getting ready -- How to do it ... -- How
it works ...
505 8 Chapter 3: Loading and Unloading Data -- Technical
requirements -- Loading data from Amazon S3 using COPY --
Getting ready -- How to do it ... -- How it works ... --
Loading data from Amazon EMR -- Getting ready -- How to do
it ... -- Loading data from Amazon DynamoDB -- Getting
ready -- How to do it ... -- How it works ... -- Loading
data from remote hosts -- Getting ready -- How to do it
... -- Updating and inserting data -- Getting ready -- How
to do it ... -- Unloading data to Amazon S3 -- Getting
ready -- How to do it ... -- Chapter 4: Data Pipelines --
Technical requirements
505 8 Ingesting data from transactional sources using AWS DMS --
Getting ready -- How to do it ... -- How it works ... --
Streaming data to Amazon Redshift via Amazon Kinesis
Firehose -- Getting ready -- How to do it ... -- How it
works ... -- Cataloging and ingesting data using AWS Glue
-- How to do it ... -- How it works ... -- Chapter 5:
Scalable Data Orchestration for Automation -- Technical
requirements -- Scheduling queries using the Amazon
Redshift query editor -- Getting ready -- How to do it ...
-- How it works ... -- Event-driven applications using
Amazon EventBridge and the Amazon Redshift Data API
520 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 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.
588 0 Print version record.
590 O'Reilly|bO'Reilly Online Learning: Academic/Public
Library Edition
650 0 Data warehousing.
650 0 Cloud computing.
650 6 Entrepôts de données (Informatique)
650 6 Infonuagique.
650 7 Cloud computing|2fast
650 7 Data warehousing|2fast
700 1 Arumugam, Thiyagarajan,|eauthor.
700 1 Patel, Harshida,|eauthor.
776 08 |iPrint version:|aWORLIKAR, SHRUTI. ARUMUGAM,
THIYAGARAJAN. PATEL, HARSHIDA.|tAMAZON REDSHIFT COOKBOOK.
|d[Place of publication not identified] : PACKT PUBLISHING
LIMITED, 2021|z1800569688|w(OCoLC)1249072610
856 40 |uhttps://ezproxy.naperville-lib.org/login?url=https://
learning.oreilly.com/library/view/~/9781800569683/?ar
|zAvailable on O'Reilly for Public Libraries
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938 ProQuest Ebook Central|bEBLB|nEBL6670232
938 EBSCOhost|bEBSC|n2956801
994 92|bJFN