In this session, we will take a look at how AWS storage services can be used to build highly scalable and resilient data lakes and data meshes to store, process, and analyze geospatial data. We will explore services like Amazon S3, Amazon Athena, AWS Glue and other relevant AWS services that form the basis of AWS data lake and data mesh architecture, and how these services accelerate the delivery of data lakes and data meshes, shortening the deployment time to production from several months to a few weeks. We will also explore geospatial specific services on AWS, including (ALS, Native geospatial support in Amazon Redshift and Sagemaker for Geospatial Ml/AI workloads) and will provide AWS Customer examples working with ESA.

The session will answer the following key questions:

1. What are the advantages of building geospatial data lakes and data meshes on AWS?

2. Which AWS storage and database services support structured GIS data?

3. Which AWS storage and database services support unstructured GIS data?

4. Which analytics capabilities does AWS provide for geospatial data?

2. Generative AI + Space

Generative AI is expected to become a $ 1.3B market by 2023, growing from less than 1 % of the global IT market today to over 10 %. Many industries, including the space industry, are wondering how they can use this new technology to improve existing projects as well as develop novel solutions. In this presentation, attendees will learn about generative AI, AWS services that help customers build generative AI applications, and the types of space mission use cases that can benefit from integrating generative AI.