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Geospatial analytics has evolved beyond analyzing static maps. Today, government agencies have access to massive volumes of diverse data including high-res images, streaming video, GPS data, and more. By applying advanced analytics to these geospatial datasets, agencies can deliver on a broad range of use cases from transportation planning to disaster recovery and population health management.

While many agencies have invested in geospatial data, few have the proper technology architecture to prepare these large, complex datasets for downstream analytics. Furthermore, most agencies lack the expertise needed to take full advantage of popular open-source spatial frameworks like GeoSpark, GeoMesa, GeoTrellis, RasterFrames, and GeoPandas for advanced analytics and deep learning, inhibiting their ability to build AI applications.

Join our technical breakfast seminar to network with your peers and learn how to easily overcome the challenges of processing and analyzing large geospatial datasets in the cloud with a unified approach to data and analytics. The discussion will cover:

• Common geospatial use cases spanning public safety, defense, infrastructure management, health services, fraud prevention and more
• Challenges analyzing large volumes of geospatial data
• How Databricks and open-source tools can be used to overcome these challenges
• Live demos that will illustrate:
• Preparing and processing geospatial data (raster and vector) at scale
  
• Techniques for optimizing geospatial predicates across massive datasets
  
• Object detection in satellite imagery using deep learning
  

Space is limited for this event. Sign up today to request a seat!