Best Practices for Processing and Visualizing Geospatial Data in Snowflake

Processing geospatial data is often challenging because it comes from diverse sources, is stored in various formats, and uses different coordinate systems to understand spatial relationships between various features. Many companies struggle to activate their geospatial data into insights. Snowflake can support advanced geospatial processing with native SQL functions and Python UDFs.

Join us in this webinar to learn how you can

• Ingest and process geospatial data from GeoTiffs and Shapefiles
• Read geospatial data using Python UDFs
• Join different sources using nearest neighbor approaches
• Handle larger images efficiently with techniques like resampling and filtering
• Visualize geospatial data using Streamlit, QGIS, and H3 functions

By the end of this webinar, you will understand how to prepare data from satellite imagery and shapefiles for machine learning models and advanced spatial analysis within Snowflake.