Organisations have access to massive volumes of geospatial data these days. By applying advanced analytics to these datasets, organisations can deliver on a broad range of use cases like mining exploration, oil discovery, asset inspection, flood surveys, environment protection, facility management, transportation planning, fraud detection, etc.
While many organisations have invested in geospatial datasets, few have the proper technology to prepare these large, complex datasets for analytics. Furthermore, most organisations are not aware of the existing open-source frameworks out there such as Apache Spark, H3, GeoMesa and Rasterframes, inhibiting their ability to analyse geospatial data at scale. Join this webinar and live demo to learn how to easily overcome these challenges with Databricks & open source tools to deliver on cutting edge geospatial use cases.
- Overview of Databricks Unified Analytics Platform.
- Types of geospatial data - how it is typically used & queried.
- Challenges analyzing large volumes of geospatial data with legacy architectures.
- How Databricks and various open-source tools can be used to overcome these challenges in the cloud
Meet with Spark and Databricks experts online and get your most pertinent questions answered in our live Q&A.
Live demos on:
Scalable Geospatial Data Analysis: Ingesting and analyzing millions of vehicle rides with H3, and visualizing your spatial data with Kepler.gl
Example notebook code to help process raster data using rasterframes