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Geospatial Data Analytics on AWS

You're reading from   Geospatial Data Analytics on AWS Discover how to manage and analyze geospatial data in the cloud

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Product type Paperback
Published in Jun 2023
Publisher Packt
ISBN-13 9781804613825
Length 276 pages
Edition 1st Edition
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Authors (3):
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Scott Bateman Scott Bateman
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Scott Bateman
Jeff DeMuth Jeff DeMuth
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Jeff DeMuth
Janahan Gnanachandran Janahan Gnanachandran
Author Profile Icon Janahan Gnanachandran
Janahan Gnanachandran
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Toc

Table of Contents (23) Chapters Close

Preface 1. Part 1: Introduction to the Geospatial Data Ecosystem
2. Chapter 1: Introduction to Geospatial Data in the Cloud FREE CHAPTER 3. Chapter 2: Quality and Temporal Geospatial Data Concepts 4. Part 2: Geospatial Data Lakes using Modern Data Architecture
5. Chapter 3: Geospatial Data Lake Architecture 6. Chapter 4: Using Geospatial Data with Amazon Redshift 7. Chapter 5: Using Geospatial Data with Amazon Aurora PostgreSQL 8. Chapter 6: Serverless Options for Geospatial 9. Chapter 7: Querying Geospatial Data with Amazon Athena 10. Part 3: Analyzing and Visualizing Geospatial Data in AWS
11. Chapter 8: Geospatial Containers on AWS 12. Chapter 9: Using Geospatial Data with Amazon EMR 13. Chapter 10: Geospatial Data Analysis Using R on AWS 14. Chapter 11: Geospatial Machine Learning with SageMaker 15. Chapter 12: Using Amazon QuickSight to Visualize Geospatial Data 16. Part 4: Accessing Open Source and Commercial Platforms and Services
17. Chapter 13: Open Data on AWS 18. Chapter 14: Leveraging OpenStreetMap on AWS 19. Chapter 15: Feature Servers and Map Servers on AWS 20. Chapter 16: Satellite and Aerial Imagery on AWS 21. Index 22. Other Books You May Enjoy

Using Geospatial Data with Amazon Redshift

Querying geospatial data in a data warehouse isn’t anything new, but the advantage of doing so in the cloud has opened the door to unparalleled performance and insight. I have heard from numerous customers who said that when they moved from their on-premises data warehouse to Redshift, they not only saved money but were also able to store and analyze more data exponentially. When you combine the cheap and efficient storage of S3 with the power of Redshift, where you can create up to 128 Redshift instances in a cluster, you can unlock powerful analytics. Also, like everything on AWS, you can then turn off those 128 instances after your query has completed and pay next to nothing. In this chapter, we will cover Redshift features as well as offer a demonstration of setting up and running geospatial queries on Redshift.

The chapter covers the following topics:

  • What is Redshift?
  • Understanding Redshift partitioning
  • Redshift...
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