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Amazon Redshift Cookbook

Amazon Redshift Cookbook

By : Shruti Worlikar, Arumugam, Patel
4.8 (9)
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Amazon Redshift Cookbook

Amazon Redshift Cookbook

4.8 (9)
By: Shruti Worlikar, Arumugam, Patel

Overview of this book

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.
Table of Contents (13 chapters)
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Extending a data warehouse using Amazon Redshift Spectrum

Amazon Redshift Spectrum allows Amazon Redshift customers to query data directly from an Amazon S3 data lake. This allows us to combine data warehouse data with data lake data, which makes use of open source file formats such as Parquet, comma-separated values (CSV), Sequence, Avro, and so on. Amazon Redshift Spectrum is a serverless solution, so customers don't have to provision or manage it. It allows customers to perform unified analytics on data in an Amazon Redshift cluster and data in an Amazon S3 data lake, and easily create insights from disparate datasets.

Getting ready

To complete this recipe, you will need the following to be set up:

  • An IAM user with access to Amazon Redshift
  • An Amazon Redshift cluster deployed in the eu-west-1 AWS Region with the retail dataset created from Chapter 3, Loading and Unloading Data, using the Loading data from Amazon S3 using COPY recipe
  • Amazon Redshift cluster...

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