Many analysts hit a ceiling when raster datasets outgrow their local machines. Processing slows down, memory runs out, and deadlines slip. This course gives you the practical skills to move past those limits by setting up cloud-based raster workflows on AWS.

Scale in the Cloud

Scale in the Cloud
This course is part of Geospatial Visualization, Cloud & Real-Time Pipelines Specialization

Instructor: ansrsource instructors
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There are 3 modules in this course
In this module, you will set up a cloud-based compute environment for raster processing on AWS. You will launch an EC2 instance, install and configure GDAL, and verify that the environment is ready for production raster workloads.
What's included
2 videos1 reading1 assignment
In this module, you will learn how to evaluate whether cloud-based raster processing delivers meaningful performance benefits compared to local execution. You will run the same raster processing task in both environments, measure execution time and resource usage, and interpret the results.
What's included
2 videos1 reading1 assignment
In this module, you will upload raster datasets to Amazon S3, organize them for analytical access, and apply lifecycle policies to control storage costs as data ages. You will configure transition rules that automatically move older rasters to cheaper storage tiers and validate that the policies work as expected.
What's included
2 videos1 reading2 assignments
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