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Amazon Redshift Cookbook

You're reading from  Amazon Redshift Cookbook

Product type Book
Published in Jul 2021
Publisher Packt
ISBN-13 9781800569683
Pages 384 pages
Edition 1st Edition
Languages
Authors (3):
Shruti Worlikar Shruti Worlikar
Profile icon Shruti Worlikar
Thiyagarajan Arumugam Thiyagarajan Arumugam
Profile icon Thiyagarajan Arumugam
Harshida Patel Harshida Patel
Profile icon Harshida Patel
View More author details

Table of Contents (13) Chapters

Preface 1. Chapter 1: Getting Started with Amazon Redshift 2. Chapter 2: Data Management 3. Chapter 3: Loading and Unloading Data 4. Chapter 4: Data Pipelines 5. Chapter 5: Scalable Data Orchestration for Automation 6. Chapter 6: Data Authorization and Security 7. Chapter 7: Performance Optimization 8. Chapter 8: Cost Optimization 9. Chapter 9: Lake House Architecture 10. Chapter 10: Extending Redshift's Capabilities 11. Other Books You May Enjoy Appendix

Chapter 3: Loading and Unloading Data

In this chapter, we will delve into the data loading process, which allows us to put transformed data from source systems into a target data warehouse table structure. While data can be loaded into Amazon Redshift using an INSERT statement (as in the case of other relational databases), it is more efficient to bulk load the data, given the volumes that a data warehouse handles. For example, in an ordering system-based data warehouse table, usually, the entire previous day's worth of data needs to be loaded rather than individual orders. Similarly, data from the data warehouse can be exported to other applications in bulk using the unload feature.

There are multiple ways of loading data into an Amazon Redshift cluster. The most common way is using the COPY command to load data from Amazon S3. This chapter will cover all the different ways you can load data into a Redshift cluster from different sources.

The following recipes will be...

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