ArcGIS GeoAnalytics Engine in Databricks: Scalable Geospatial Analysis in a Data Science Workflow

Esri and Databricks collaborated on a blog that features advanced spatial capabilities of ArcGIS GeoAnalytics Engine in an Azure Databricks environment solving cross-industry use cases. Databricks provides an Apache Spark-based cloud platform to support big data analytics, data science and machine learning in a unified approach by combining data warehouses and data lakes into a lakehouse architecture. GeoAnalytics Engine brings geospatial analysis straight to your big data in the cloud wherever it lives—in a data warehouse, data lake, and more. The goal of this collaboration was to demonstrate how easily ArcGIS GeoAnalytics Engine can be plugged into Databricks architecture to extend cloud-based geospatial capabilities for organizations that need big data spatial solutions at speed and scale.

Read the blog to discover how combining the power of GeoAnalytics Engine in a Databricks environment enabled challenging use cases to be solved.

About the authors

Arif Masrur, PhD

Arif Masrur is a Sr. Solutions Engineer for Esri's Data Science and Advanced Analytics capability. Arif received a PhD in Geography (Specialized in GIScience) from Penn State, an MA in Geography (GIS and Cartography) from University of Northern Iowa, an MS and a BS in Geography and Environment from University of Dhaka, Bangladesh.

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Corinne Walker

Corinne is a Product Marketing Manager on Esri’s Spatial Analytics & Data Science team. She has a background in marketing and business analytics with experience working in the technology and geospatial industries.

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