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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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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

Summary

In this chapter, we discussed the cloud-native database Amazon Aurora. This modern database technology is much easier to set up than servers in a traditional data center and provides compatibility with familiar tools and concepts to store and manage your geospatial data in a relational database. PostGIS is the most widely used extension to provide storage, functions, and management of your geospatial data. The connectivity to your database can be configured for wide or narrow access to meet the requirements of your specific use case to achieve the right combination of accessibility and security.

You have seen examples of how to quickly load shapefile data into a PostgreSQL database extended with PostGIS. Having all of this data cataloged and structured in AWS enables a wide range of processing capabilities. In the next chapter, we’ll delve into geoprocessing and transforming your data at scale using the power of the cloud. Serverless processing on a secure global...

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