09-10, 10:30–11:00 (America/Chicago), Grand B
What does it mean to be cloud-native in the context of geospatial data? This talk will cover how to leverage scalable compute and cloud-native data formats for high performance and large-scale geospatial analytics with Apache Sedona.
This talk will cover the architecture and benefits of the open-source Apache Sedona project including use cases for gaining insights from geospatial data at scale such as raster data analysis like zonal statistics, spatial joins, and applying machine learning to satellite imagery with raster inference. We discuss the challenges that can arise when working with geospatial data at scale and Apache Sedona is architected to address these challenges. Finally, we examine how leveraging cloud-native data formats like GeoParquet and Apache Iceberg can enable large-scale geospatial analytics.
