Amazon redshift cookbook: recipes for building modern data warehousing solutions
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 developmen...
Gespeichert in:
| Beteiligte Personen: | , , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | Englisch |
| Veröffentlicht: |
Birmingham
Packt Publishing, Limited
2021
|
| Schlagwörter: | |
| Links: | https://learning.oreilly.com/library/view/-/9781800569683/?ar |
| Zusammenfassung: | 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. |
| Beschreibung: | Print version record |
| Umfang: | 1 Online-Ressource |
| ISBN: | 9781800561847 1800561849 9781800569683 |
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| spelling | Worlikar, Shruti VerfasserIn aut Amazon redshift cookbook recipes for building modern data warehousing solutions Shruti Worlikar, Thiyagarajan Arumugam, Harshida Patel Birmingham Packt Publishing, Limited 2021 1 Online-Ressource Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Print version record 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. Data warehousing Cloud computing Entrepôts de données (Informatique) Infonuagique Arumugam, Thiyagarajan VerfasserIn aut Patel, Harshida VerfasserIn aut 1800569688 Erscheint auch als Druck-Ausgabe 1800569688 |
| spellingShingle | Worlikar, Shruti Arumugam, Thiyagarajan Patel, Harshida Amazon redshift cookbook recipes for building modern data warehousing solutions Data warehousing Cloud computing Entrepôts de données (Informatique) Infonuagique |
| title | Amazon redshift cookbook recipes for building modern data warehousing solutions |
| title_auth | Amazon redshift cookbook recipes for building modern data warehousing solutions |
| title_exact_search | Amazon redshift cookbook recipes for building modern data warehousing solutions |
| title_full | Amazon redshift cookbook recipes for building modern data warehousing solutions Shruti Worlikar, Thiyagarajan Arumugam, Harshida Patel |
| title_fullStr | Amazon redshift cookbook recipes for building modern data warehousing solutions Shruti Worlikar, Thiyagarajan Arumugam, Harshida Patel |
| title_full_unstemmed | Amazon redshift cookbook recipes for building modern data warehousing solutions Shruti Worlikar, Thiyagarajan Arumugam, Harshida Patel |
| title_short | Amazon redshift cookbook |
| title_sort | amazon redshift cookbook recipes for building modern data warehousing solutions |
| title_sub | recipes for building modern data warehousing solutions |
| topic | Data warehousing Cloud computing Entrepôts de données (Informatique) Infonuagique |
| topic_facet | Data warehousing Cloud computing Entrepôts de données (Informatique) Infonuagique |
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